Management Blood Using Optimization Algorithm: A State of the Art

Literature Review

Menur Wahyu Pangestika, Zalilah Abd Aziz and Razulaimi Bin Razali

College of Computing Informatics and Media, Universiti Teknologi MARA (UiTM), Selangor Darul Ehsan, Malaysia

Keywords:

Blood Management, Optimization Algorithm, Blood Transportation.

Abstract:

Blood is an important element that beneﬁts every human being and is the most valuable resource in any health

institutions. Blood transfusion service to patients is one of the health efforts for disease healing and health

recovery which urgently requires the availability of blood and blood components. These blood components

need to be sufﬁcient, safe, easily accessible, and affordable by the community. Blood management is a series of

activities that involves planning, organizing, coordinating, and controlling the provision of blood at the blood

centre. The activities started from donating the blood, securing and processing the blood components, storing

and distributing of blood to hospitals that requires the blood. In this paper, 45 articles published from 1973-

2021 that discussed the problems that exist in the problem of blood management were reviewed. Optimization

algorithms related to solving the blood problems were also observed. Discussion on other related topics such

as blood organization, blood transportation, and factors for clinical blood loss were also included.

1 INTRODUCTION

The key to an effective health system is the provi-

sion of safe blood services and adequate blood prod-

uct (Organization, 2009). Blood is a supplied re-

source, with unpredictable demand and blood that

must always be fulﬁlled (Duan and Liao, 2014) be-

cause blood is an important element that beneﬁts ev-

ery human being (3, 2012) and is the most valuable

resource in institutions any health (Baig and Javed,

2020). If blood is not managed properly, it will spoil

quickly which will have an impact on the develop-

ment of the supply chain (Karadag and Keskin, 2021).

Blood donation plays an important role in the

blood supply chain because between donor motiva-

tion, optimization of location and capacity decisions,

and control between reliability and resilience will

be interdependent (Hosseini-Motlagh et al., 2020a).

Blood is human blood which consists of cell compo-

nents and a liquid component in the form of plasma.

Transfusion blood is blood obtained from a donor

who donates blood to a blood center. Blood centers

and hospital blood banks are separate places with dif-

ferent blood management. The provision of blood at

the blood center is a series of activities starting from

donating blood, securing blood, processing blood

components, storing blood and distributing blood to

hospitals that need blood. Because the management

of blood between the blood center and the blood bank

is different, the service for giving blood to the recipi-

ent is carried out by the hospital through the hospital’s

blood bank which gets its supply from the blood cen-

ter. A hospital blood bank is a work unit that receives

and stores blood from a blood center, performs cross-

match checks and delivers blood to be transfused to

recipients according to applicable standards.

Management is the use of resources effectively

and efﬁciently in the process of planning, organiz-

ing, coordinating, and controlling (Lloyd, 2020). One

of the health efforts of blood transfusion services for

healing disease and health restoration is the availabil-

ity of sufﬁcient blood or blood components that are

affordable to the community.

Two indicators of network performance in the hos-

pital’s integrated inventory system are in terms of

cross-matching units and obsolete units. This sup-

ply is called lateral supply which allows hospitals to

meet their demand with other hospital supplies with-

out the need for products in the blood center and ex-

cess in any hospital (Arani et al., 2021). National

Safety and Quality Health Service (NSQHS) Standard

7, Systems must be in place for healthcare organiza-

tions to safely and effectively accept, store, transport,

and monitor used blood and blood products (Commis-

sion and Care, 2012). But in reality, there are various

problems that occur in this process for example ex-

Pangestika, M., Aziz, Z. and Razali, R.

Management Blood Using Optimization Algorithm: A State of the Art Literature Review.

DOI: 10.5220/0012444600003848

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Advanced Information Scientiﬁc Development (ICAISD 2023), pages 107-117

ISBN: 978-989-758-678-1

107

pired blood (Heidari-Fathian and Pasandideh, 2018b)

(Sapountzis, 1984).

The purpose of this paper is to ﬁnd out speciﬁc

problems in blood management problems and the al-

gorithms used to solve problems in blood manage-

ment. In this paper, several problems and issues will

be presented to discuss blood management problems

which are solved by optimization theory.

There are 6 points that will be discussed in this

paper from the introduction to the conclusion. The

ﬁrst point is the introduction to the topic of this pa-

per related to blood management. The second point

that will be discussed is Background related to blood

organisation, blood transportation, and clinical blood

loss. The third point is Review methodology. The

discussion of this point is an explanation of the ar-

ticle collection process as well as a critical review

of the collected articles. The fourth point discusses

the blood management problem. The ﬁfth point dis-

cusses optimization algorithms that are applied to

solve blood management problems. The ﬁnal section

is a conclusion that discusses all the work presented

in this paper.

2 BACKGROUND

Patient Blood Management is a clinical and multidis-

ciplinary approach to optimizing patient care requir-

ing blood transfusions. Blood management is a long

chain of processes so it can have problems that can

disrupt the integrity of the process chain (Markowitz

et al., 2014). The problem of blood management in

the journal found is solved by optimization. The rea-

son is that optimization is one of the disciplines in

mathematics that is used to solve problems such as

minimal costs, maximum proﬁts, optimal design, op-

timal management, and minimal errors (Dijk et al.,

2009).

Blood types are A, B, AB, and O blood. Peo-

ple who donate blood will go through a selection test

process ﬁrst to ﬁnd out whether potential donors can

donate blood or not. If the potential donor has met

the criteria, then the prospective donor can donate

blood. Lack of blood can occur due to several things.

Sometimes there are many donors who want to donate

blood but do not pass the selection test to be able to

donate blood or request a blood type from the hospital

to the blood center with the availability of the blood

type in the blood center is not appropriate, while for

other blood types there are large amounts.

Blood components whole blood, RBCs, Platelets,

and Plasma (Gurevitz, 2010) have their respective

ages and use. Whole blood has an age of up to 30 days

which is used for trauma and surgery cases. RBCs

have an age of up to 42 days and are used for cases

of anemia, surgery, trauma, blood disorder, any blood

loss, and such as sickle cell. Platelets have an age of

up to 5 days and are used for cases of cancer treat-

ments, organ transplants, and surgery. Plasma has a

lifespan of up to 24 months for burn patients, shock,

and bleeding disorders (Ahmadi et al., 2017). Blood

components are used for various treatments (Shih and

Rajendran, 2020).

At the hospital, each department will request

blood based on blood components and type. Doctors

will tend to ask for more blood bags for patient safety,

causing uncertain blood needs. If later after the blood

bag has been used and there are excess blood bags,

the blood bag will be given or transferred to another

patient with the same blood group and component.

However, if the blood is not used by another patient

until the expiration date, then the blood will be dis-

carded

2.1 An Overview of Blood Organization

Implementation of the provision of national blood

needs requires collaboration between blood transfu-

sion services, government, hospitals, mass media, and

the general public. Even in large countries, a regional

distribution of blood needs is necessary. So there is a

need for an effective national blood committee whose

function is to formulate national blood policies in-

cluding rules and regulations for storage, processing,

collection, transportation, distribution of blood, and

administration of blood transfusions to patients. Na-

tional blood transfusion services require medical and

managerial skills that are ideally led by a medically

qualiﬁed director. A large blood transfusion service

is also needed by the manager. Blood transfusion

services can be centralized, regionally hospital-based

or a combination. This system cannot be changed.

Blood collections can be organized by a blood cen-

ter, a hospital, or both. Large countries do it region-

ally where one center is responsible for the area A

centralized organization that operates transfusion ser-

vices throughout the country, with or without satellite

regional centers. Regional organization can be carried

out in two events, namely a strong national transfu-

sion center with direct control of regional blood cen-

ters or national blood transfusion centers that have

loose national coordination with regional centers. A

hospital-based organization in which each hospital

has its own blood collection program with or without

central regulation and coordination. A mixed system

is a hospital or blood service that can collect blood in-

dependently which can increase the independence of

ICAISD 2023 - International Conference on Advanced Information Scientiﬁc Development

108

the institution (Gibbs and N, 1993).

2.2 An Overview of Blood

Transportation

Blood transfusion services aim to fulﬁll patient de-

mand by offering efﬁcient, secure, and sufﬁcient

blood and blood products (Gibbs and N, 1993). Good

blood storage management includes ordering, stor-

ing, handling, and administering blood products ef-

ﬁciently and optimally. Blood management consists

of two key factors, such as product availability (blood

storage plan, delivery time, and order volume) and

product integrity (process and physical product con-

trol to ensure effective and efﬁcient handling, thereby

maintaining availability and reducing blood damage)

(Authority, 2014). The blood supply chain network

consists of donors, blood collection facilities, labora-

tories, hospitals, and blood centers (Arani et al., 2021)

(Ghorashi et al., 2020). Two important properties

are considered in the blood supply, namely the ABO-

Rh factor and the shelf life of blood products (Arani

et al., 2021). The problem with the blood supply

chain (BSC) is price management, business decisions,

and optimal design. In Turkey, the BSC management

is carried out by the Turkish Red Cross Chain. The

Turkish Red Cross is an important part of the Health

system. The Turkish Red Cross blood chain struc-

ture is responsible for the supply of blood collected

from donors via blood donation vehicles and mobile

or blood donation centers which are then transported

to the nearest regional blood center. The regional

blood center will process various laboratory tests, pro-

duce and store blood products, and deliver the blood

products to hospitals or health centers according to

their needs (Karadag and Keskin, 2021).

2.3 An Overview of Clinical Blood Loss

Red blood cells will be transfused especially in symp-

tomatic patients or when patients lose blood con-

tinuously (Allard and Contreras, 2015). Blood is

used in hematological conditions such as thalassemia,

hemophilia, leukemia, and aplastic anemia (Gibbs

and N, 1993). In addition, blood is also used for

complications of pregnancy, trauma, severe anemia

in childhood, gynecology, cancer, surgery, hemato-

logical disorders, and chronic diseases (Shamshirian

et al., 2018). Signiﬁcant blood loss and relevant

transfusions are important events in perioperative care

(Bartoszko et al., 2017). Transfusion should also

be guided by clinical signs and symptoms when the

hemoglobin is between 7-10g/dL as in concomitant

medical or surgical problems. For example in pa-

tients with age ¿65 years, cardiovascular disease, on-

going blood loss, respiratory disease, and coagulopa-

thy. So in an incident like this, the blood bank must

be able to ensure that blood and blood components are

available or sufﬁcient. When a patient is to undergo

blood transfusion, the decision depends on estimates

of how much blood loss, rate of blood loss, evidence

of end-organ dysfunction, pre-bleeding hemoglobin

level and whether there is a risk of coronary artery

disease (Allard and Contreras, 2015).

3 REVIEW METHODOLOGY

In this paper, we synthesize a knowledge base that

links the problems of blood management and op-

timization. We conducted a review in two stages,

namely (1) Framing the research objective and (2)

Study Selection.

3.1 Framing the Research Objective

There are 2 purposes of this writing, namely:

RO1: knowing the speciﬁc problems that exist in

the problem of blood management;

RO2: ﬁnd out what optimization algorithms are

used to solve blood management problems.

3.2 Study Selection

Identiﬁcation of articles that are suitable for analysis

is carried out at the study selection stage. The steps

taken are (1) determining search criteria and database,

(2) inclusion and exclusion criteria, and (3) select-

ing the relevant studies and descriptive analysis. The

ﬂowchart of the study selection is shown in Figure 1.

Figure 1: Flowchart Study Selection.

Management Blood Using Optimization Algorithm: A State of the Art Literature Review

109

3.3 Determining Search Criteria and

Database

Before the article search, we identiﬁed several key-

words that were used as literature for this writing re-

lated to the research topic. There are two groups of

keywords used for literature searches:

A. Words related to blood management: “Blood”;

”Management”; ”Blood Management”; ”Blood Orga-

nization”; “Blood Transportation”; “Clinical Blood

Loss”; “Blood Management Problems”; “Blood

Transfusion”; “Blood Donors”; “Type of Blood Prod-

ucts”; ”Blood Supply Chain”.

B. Words related to optimization: “Optimization”;

“advantages and disadvantages of optimization”; ”al-

gorithm optimization”; ”Heuristics”; “Metaheuris-

tics”; ”Optimization of Blood”.

The search carried out is to ﬁnd several journals

that discuss blood management issues. Next, do a

search on optimization studies. Finally, do a search

related to optimization to solve various blood man-

agement problems. So we found various problems

in blood management and methods for solving them.

To search this journal, we used 2 widely recognized

databases, namely Scopus and Web of Science (WoS).

3.4 Inclusion and Exclusion Criteria

In Table I below, The author analyzed by determining

the inclusion criteria and exclusion criteria in select-

ing the relevant studies

Table 1: Inclusion Criteria and Exclusion Criteria.

No. Inclusion Criteria Exclusion Criteria

1 Studies related to; Review articles;

blood management

2 Studies related Studies that have

to optimization are a theoretical or

used to solve blood conceptual

management problems. framework.

3.5 Selecting the Relevant Studies

In writing this paper, several screenings were carried

out for the study selection stage. These stages are

starting from the selection of titles and abstracts, fol-

lowed by reading the entire text, and selecting jour-

nals for screening several journals that are in accor-

dance with the objectives of the research.

The ﬁrst stage is the selection of titles and ab-

stracts based on the purpose of this research and seen

from several keywords that are appropriate to the re-

search. Next, we apply journal selection based on in-

clusion and exclusion criteria. Followed by reading

the full-text version used as literature in this study.

The papers used are papers published in 1973-2021.

3.6 Descriptive Analysis

The number of papers published in this ﬁeld is an

ever-increasing number of blood management prob-

lems from distribution to storage. Figure 2 shows that

there are various solutions or algorithms used to solve

blood management problems and including optimiza-

tion algorithms. From this graph, it can be seen that

from 1973 until 2021 the resolution of this problem

for several studies is still being carried out.

Figure 2: Distribution of Reference Papers by Year.

3.7 An Overview of Optimization

Algorithm

Optimization is an act or process of making the best of

something; (also) the optimal rendering action or pro-

cess; optimal state or condition (oxford dictionary).

Optimization is to help human activities in solving

problems such as creating, and processing an optimal

product design, but optimization can also be used for

problems such as mathematics in calculating minimal

costs, and maximum proﬁts, making an optimal de-

sign, and optimal management (Kulkarni, 2017). In

optimization, there are two categories, such as Ap-

proximate which can provide the right solution or not

provide the right solution. The second is Exact which

can provide exact solutions (Dr

eo and Siarry, 2003).

4 BLOOD MANAGEMENT

PROBLEM

Several management problems, including blood dis-

tribution, can be seen.

1. Citation: (Haijema et al., 2007)

Method: “Combined Markov Dynamic Program-

ming (MDP) And Simulation” Type of Blood

Product: Platelet

ICAISD 2023 - International Conference on Advanced Information Scientiﬁc Development

110

Issue: Demand is highly variable and uncertain;

Cost production; Stock time ex- pired.

Objective: Presenting dynamic program- ming

formulations for blood platelet problems; Pro-

vides optimal numerical computation and policy

structures for small-sized situations; The ”nearp-

timality” of singlelevel and double-level order-up-

to policies should be demonstrated; Offers a sim-

ulation based search algo- rithm; Make sure it’s

okay to ignore different blood types.

2. Citation: (Dijk et al., 2009)

Method: “A Mathematical Technique Called

Stochastic Dynamic Programming (SDP) And

Computer Simulation”

Type of Blood Product: Platelet

Issue: Shortages; Overproduction; Outdating;

Cost Production.

Objective: Presents an approach based on op-

erations research techniques on blood manage-

ment; Provides formal support for the existence of

nearoptimal upto order rules and a structural and

replicable approach to computing them; Apply an

operations research approach to actual inventory

data to obtain a number of interesting conclusions

for blood management

3. Citation:(Ghandforoush and Sen, 2010)

Method: DSS, Integer Nonlinear Programming

Type of Blood Product:Platelet

Issue: Platelets have a very short shelf life

Objective: ”Determine the minimum cost

platelet production schedule at the regional blood

center with the time that is every day of the week”

4. Citation: (Osorio et al., 2017)

Method: “Combines Discrete-Event Simulation

(DES) With Integer Linear Programming (ILP)”

Type of Blood Product: Platelet

Issue: Uncertain supply and demand; Shelf life

constraints.

Objective: Calculating temporary production

costs

5. Citation: (Jabbarzadeh et al., 2014)

Method: Supply Chain Network,Robust Opti-

mization

Type of Blood Product: Blood Product

Minimize the total cost of the network; The un-

certain and dynamic nature of blood demand

Minimize total network cost

6. Citation: (Duan and Liao, 2014)

Method: A Simulation Optimization (SO), TA-TS

(Threshold accepting- Tabu search)

Type of Blood Product: Red blood cell, Blood

ABO

Issue: Outdating

Objective: Minimize the expected system expiry

rate below the maximum pre-determined allow-

able deﬁciency level

7. Citation: (Dillon et al., 2017b)

Method:“Two-Stage Stochastic Programming

Model”

Type of Blood Product: Blood Product

Issue: Uncertainty in the demand; Perishable

blood; Minimize operational costs; Lack and

waste of blood due to expiration.

Objective: Minimize operational costs, as well

as shortages and wastage of blood due to ob-

solescence, taking into account durability and

uncertainty of demand.

8. Citation: (Attari et al., 2019)

Method: “Blood Supply Chain; Stochastic Pro-

gramming; e-Constraint; Robust Optimization”

Type of Blood Product: Blood Product

Issue: Minimize the expected costs; Uncertainty

Objective: Developing a novel hybrid approach.

9. Citation: (Heidari-Fathian and Pasandideh,

2018b)

Method: “Multi-Objective Optimization, Robust

Optimization, Bounded Objective Function,

Lagrangian Relaxation”

Type of Blood Product: Blood Product

Issue: Minimize the total cost; Demand for the

blood product are uncertain.

Objective: Minimize the total costs of the supply

chain network; Proposed for minimizing the total

number of shortages and perished blood products;

minimize the total amount of GHG emissions

caused by transportation activities in the chain.

10. Citation: (HosseiniFard and Abbasi, 2016)

Method: Two Echelon Inventory,Stochastic Re-

plenishment

Type of Blood Product: Blood Product

Issue: Perishable items.

Objective: ”shows how centralizing hospital in-

ventory in the second echelon of the blood supply

chain and two echelons with perishable goods to

improve supply chain performance when replen-

ishment is stochastic”.

11. Citation: (Heidari-Fathian and Pasandideh,

2018a)

Method: Mixed-Integer Linear Mathematical,

MultiObjective Decision Making, Augmented

eConstraint Method And LP-Metric Method,

ELECTRA

Type of Blood Product: Blood Product

Issue: Minimize the total cost

Objective: Minimizes total chain costs and

maximizes the reliability of local and primary

Management Blood Using Optimization Algorithm: A State of the Art Literature Review

111

blood centers by maximizing the total average

amount of blood products delivered to the point

of demand.

12. Citation: (Liu and Song, 2019)

Method: “A discrete-time mixed integer linear

program- ming (MILP)”

Type of Blood Product: Red blood cells

Issue: Total operational cost; Uncertainty; Perish-

able product.

Objective: Minimize the total time for central

blood collection, and blood transport; Minimize

the total cost of setting up a blood collection cen-

ter, and transporting blood.

13. Citation: (Hamdan and Diabat, 2018)

Method: “Combined Markov Dynamic Program-

ming (MDP) And Simulation”

Type of Blood Product: Red Blood Cells

Issue: Inventory; Location decisions; Reduce the

number of outdates; Simultaneous blood delivery

time and system fees Uncertainty demand.

Objective: Reduce the number of expirations, sys-

tem costs and blood delivery times simultane-

ously.

14. Citation: (Hosseini-Motlagh et al., 2020b)

Method: “Multi-Objective Optimization, Robust

Fuzzy Stochastic Programming”

Type of Blood Product: Blood Product

Issue: Minimizing the shortage and wastages; Un-

certainty; The perishability of blood; The age-

based characteristic of blood.

Objective: Minimize the expected value of the to-

tal shortage including the shortage of fresh blood

in the hospital blood bank (HBB), the shortage

of ordinary blood in the HBB, the shortage of

fresh blood in the area, and the short- age of or-

dinary blood in the area during all periods; Mini-

mize the total cost of SC which consists of the

ﬁxed costs of opening TES in the regions, the cost

of purchasing fresh blood and ordinary blood at

HBB, the cost of purchasing fresh blood and or-

dinary blood sent to the regions, and the cost of

waste and storage at HBB.

15. Citation: (Rajendran and Ravindran, 2019)

Method: Modiﬁed Stochastic Genetic Algorithm

(MSGA)

Type of Blood Product: Platelet

Issue: Wastage; Shortage.

Objective: Minimize Wastage and Shortage

In general, the blood management problems that

occur are related to three points in Jennings’ jour-

nal in 1973. The paper that will be discussed

is various obstacles related to blood management

problems in 1973-2021. One of the problems in

supply chain management is the management of

perishable blood products, because the blood cen-

ter is responsible for receiving, transfusing, and ﬁ-

nally delivering blood products to the point of de-

mand (Heidari-Fathian and Pasandideh, 2018b).

Many complex factors occur in the blood sup-

ply such as uncertain supply and demand, the

proportion of blood groups, shelf life limitations,

and different collection and production methods

(Heidari-Fathian and Pasandideh, 2018b; Osorio

et al., 2017; HosseiniFard and Abbasi, 2016). Be-

cause the nature of blood is perishable, it is nec-

essary to consider the time required to process

the received blood and minimize the amount of

wasted blood (Alizadeh et al., 2020).

16. Citation: (Larimi and Yaghoubi, 2019)

Method: Robust-Stochastic Optimization

Type of Blood Product: Platelet

Issue: Demand ﬂuctuation; Short lifespan of

platelets; Efﬁciency as suppliers and costs

Formulate the cost of placing BET in the hospital

plus the cost of setting up ﬁxed produc- tion in the

laboratory center.

17. Citation: (Alizadeh et al., 2020)

Method: Bi-Objective

Type of Blood Product: Blood Product

Issue: Highly perishable; Time Processing; Mini-

mizing the amount of wasted blood.

Objective: Consider the economic dimension of

the supply chain; Minimize blood transfusion

times from portable facilities to hospitals.

18. Citation: (Ahmadimanesh et al., 2020)

Method: Deep Neural Network

Type of Blood Product: Blood Product

Issue: Expired blood; Blood perishability; Uncer-

tainty of blood demand; Reducing blood return

and blood loss

Objective: Designing an optimal blood transfu-

sion network manage- ment model and deep neu-

ral network that is used so that the cost of blood

waste, return and shortage can be reduced by sev-

eral recursive layers in the supply chain

19. Citation: (Shih and Rajendran, 2020)

Method: Possibilistic Programming; P-

Robustness

Type of Blood Product: Blood Product

Issue: Maintaining sufﬁcient blood supply; Blood

Wastage

Objective: Develop a novel mixed possibilistic-

stochastic ﬂexible robust programming

20. Citation: (Abdulwahab and Wahab, 2014)

Method: Approximate dynamic programming

Type of Blood Product: Platelet

ICAISD 2023 - International Conference on Advanced Information Scientiﬁc Development

112

Issue: Blood platelet shortage; Outdating; Inven-

tory level

Objective: Minimizes deﬁciency and wastage of

blood platelets while maximizing the total reward;

Keep inventory levels to a minimum by meeting

various types of demand using appropriate poli-

cies.

21. Citation: (Sapountzis, 1984)

Method: Integer Programming Model

Type of Blood Product: Blood Product

Issue: Expired Blood

Objective: Minimize the number of units of blood

that will be sent back to the blood transfusion ser-

vice when the blood expires.

22. Citation: (Shih and Rajendran, 2020)

Method: A Stochastic Mixed-Integer Linear Pro-

gramming (MILP)

Type of Blood Product: Platelet

Issue: easily damaged elements; Age limit of

platelets and red blood cells; Uncertainty of sup-

ply; supply costs; Lack of blood and; Expired

wastage of blood

Objective: Minimize the total costs incurred

throughout the blood supply chain.

Is responsible for receiving, transfusing, and ﬁnally

delivering blood products to the point of demand

(Heidari-Fathian and Pasandideh, 2018a). Many

complex factors occur in the blood supply such as un-

certain supply and demand, the proportion of blood

groups, shelf life limitations, and different collection

and production methods (Heidari-Fathian and Pasan-

dideh, 2018b) (Osorio et al., 2017) (HosseiniFard and

Abbasi, 2016). Because the nature of blood is perish-

able, it is necessary to consider the time required to

process the received blood and minimize the amount

of wasted blood (Alizadeh et al., 2020).

Several papers discuss blood problems with blood

patelets components. Platelets are components of

blood that are easily damaged they have a very short

shelf life (Abdulwahab and Wahab, 2014) and need

to pay attention to the amount of demand and supply

(Ghandforoush and Sen, 2010) with a shelf life of 5-

7 days. The demand for platelet blood is uncertain

and its production is periodic in one week, so efforts

need to be made so that there is no shortage or ex-

cess (Haijema et al., 2007). If there is uncertainty

in the demand for blood platelets, it will cause a sig-

niﬁcant waste of the total blood collected by donors

(Rajendran and Ravindran, 2019). Uncertain blood

demand needs to be minimized in order to avoid over-

production which can lead to expiration (Dijk et al.,

2009). In addition, it is necessary to develop an ap-

propriate inventory model in order to minimize the

shortage and waste of blood (Rajendran and Ravin-

dran, 2019). In addition, from the transportation side,

the following paper discusses transportation schedule

for the delivery of platelets from the production center

to the transfusion center, which is usually a hospital

(Ghandforoush and Sen, 2010).

The number of donor platelets in the supply chain

can be affected by four main issues namely the pres-

ence of different types of donors as polycythemi-

adonors for the ﬁrst time, the number of donors or-

dered and the number of donors not ordered during

and after, allocation of blood extraction technology to

hospitals, and sending announcements. social media

such as social media, newspapers and banners (Larimi

and Yaghoubi, 2019).

One of the properties of blood is that blood has a

shelf life and if it exceeds the production limit it will

expire. So that several papers have discussed about

minimizing the expiry rate. Blood supply managers

in the blood supply always try to keep blood products

sufﬁcient and to reduce the number of deaths due to

expired blood (Ahmadimanesh et al., 2020). This pa-

per uses RBC blood components which have a shelf

life of up to 42 days. RBC is useful for patients with

chronic anemia, kidney failure, gastrointestinal bleed-

ing, and acute blood loss due to trauma and surgery

(Duan and Liao, 2014). Reducing the number of

expiry dates, system costs, and the time of sending

blood simultaneously are also discussed in the paper

(Hamdan and Diabat, 2018). The blood component

used in this study is red blood cells. This research

accounts for the production, inventory, and location

decisions. Due to the perishable nature of blood prod-

ucts, the storage of large quantities of blood prod-

ucts is limited and the quality of blood products de-

creases with transportation time. Blood is also needed

in times of disaster. The following paper discusses

the determination of the allocation and location of

blood facilities for several post-disaster periods (Dil-

lon et al., 2017b). In addition, during a disaster, the

need for an efﬁcient blood supply is more important.

This occurs when there is no coordination between

distribution and inventory management.

Blood supply planning can help inventory to make

decisions under uncertainty, to minimize blood short-

ages and waste (Hosseini-Motlagh et al., 2020b). In

addition, when a disaster occurs, it is necessary to

manage the blood supply chain system optimally in

terms of determining the amount of blood collection,

location, transportation, and storage in order to min-

imize the total response time and total operational

costs (Liu and Song, 2019).

Other papers discuss the various characteristics of

blood requests, i,e, the existence of uncertain blood

requests that cause blood shortages and wastage. per-

Management Blood Using Optimization Algorithm: A State of the Art Literature Review

113

ishable nature of blood, strong subjective bias towards

criteria other than cost minimization and Minimizing

operational costs (Dillon et al., 2017a).

In addition, another paper discusses the prob-

lem of blood management, called Perishable element,

Platelets having a limited lifetime of ﬁve days and red

blood cells lasting 42 days, Supply uncertainty, Sup-

ply cost, Shortage of blood and Expired wastage of

blood (Shih and Rajendran, 2020).

Some of the papers that have been described, until

2021 are still discussing some blood problems from

storage, organization to distribution of the blood it-

self.

5 OPTIMIZATION ALGORITHM

ON BLOOD MANAGEMENT

PROBLEM

Several studies use optimization to solve blood prob-

lems. Ghorashi et al, used mathematical models to

solve problems related to minimizing the total cost

and supply chain time to make decisions regarding

location-allocation, blood ﬂow, inventory levels, and

optimal routes. The problem is solved by optimiza-

tion using the Multi-Objective Gray Wolf Optimizer

algorithm which is compared with two algorithms,

such as Multi-Objective Particle Swarm Optimiza-

tion and Non-dominated Sorting Genetic Algorithm-

II. After conducted statistical tests, it was found that

the Multi-Objective Gray Wolf Optimizer can solve

problems efﬁciently and can outperform other ap-

proaches (Ghorashi et al., 2020).

Blood management system related to the entry and

exit of blood, related to planning, implementation,

and control. Another study uses mathematical mod-

els and metaheuristic optimization methods that offer

a better solution approach for blood allocation in a dy-

namic environment. This study uses red blood cells.

The optimization method used is to combine symbi-

otic organisms search, genetic algorithm, and particle

swarm optimization (Ezugwu et al., 2020).

The next research, implements the particle swarm

optimization algorithm, the results of which show the

ability to minimize the import of blood units, and

there is no form of waste (Adewumi et al., 2012).

W. Liu et al (2020) found blood has an easy expi-

ration date and blood distribution problems, this paper

optimizes the blood product scheduling scheme using

the concept of a vendor-managed inventory routing

problem (VMIRP).

The concept is used to balance supply and demand

to minimize operational costs. The decomposition al-

gorithm is also used to solve the proposed mathemat-

ical model. By using this concept, it is found that the

VMIRP concept can reduce the operational costs of

the blood supply chain.

To overcome the problem of perishable blood,

this paper designs a two-stage approach, the strategic

stage and the tactical stage, which create two models

to obtain location-allocation decisions and to obtain

inventory control decisions from the optimal quantity

of blood ﬁlling. To solve this problem, the optimiza-

tion algorithm used is the Genetic Sorting II (NSGA-

II) algorithm which is not dominated to ﬁnd Pareto

sets (Hsieh, 2014).

The uncertain demand for blood products has

also been investigated and solved using a multi-

objective mixed integer mathematical programming

model. The model aims to minimize the total cost

of the supply chain network. Optimization algo-

rithms used to solve this problem are bounded objec-

tive function, robust optimization, and Lagrangian re-

laxation (Heidari-Fathian and Pasandideh, 2018b).

The existence of various kinds of demand for

blood becomes a strategic problem in choosing the

best combination of technology. Many factors are en-

countered in blood problems whose solutions utilize

optimization to optimize the total cost and the num-

ber of donors needed. The existence of stochastic

demand, blood type compatibility, blood availability,

and blood group proportions result in uncertainty. To

solve this problem, a multi-objective stochastic inte-

ger linear programming model is used and a new com-

bination of the Average Approximation and the Aug-

mented Epsilon-Constraint algorithm is used (Muriel

et al., 2017).

Storing an excessive number of units of blood in

the blood storage can result in the wastage of blood

products. This is due to the perishable nature of

blood. A dynamic mathematical model is applied to

this problem which aims to increase the efﬁciency of

blood-related activities that occur in the blood center.

if there is a failure in the blood supply, it will result in

the cancellation of the operation and some worst-case

scenarios. An optimization algorithm is proposed to

solve this problem which aims to identify the opti-

mal routing for each blood group. These algorithms

are symbiotic organisms search, symbiotic organisms

search genetic algorithm, and symbiotic organisms

search simulated annealing algorithms (Ezugwu et al.,

2019).

So that blood can be distributed properly and the

quality of blood products can also be maintained, it

is necessary to manage distribution to various loca-

tions that need blood properly. Several papers have

discussed these problems which can be solved by op-

ICAISD 2023 - International Conference on Advanced Information Scientiﬁc Development

114

timization.

During a disaster, some locations require blood fa-

cilities and distribution of blood products after a nat-

ural disaster. At the same time, uncertainty becomes

an inseparable part of the uncertainty of the need for

blood and location during and after the disaster. The

researcher compares the P-robust optimization and ro-

bust optimization approaches. In this paper, two mod-

els are made, a model for determining the location

and a model for determining distribution decisions in

an uncertain environment. Distribution decisions take

into account how much blood should be brought to

the disaster site (Fereiduni and Shahanaghi, 2016).

The planning of transportation operations in the

blood sample supply chain, which includes clinics

and laboratories, is the emphasis of this article. This

study objective is to determine the optimal number

of vehicles to deploy and to plan the pick-up proce-

dure. The step is to develop a mixed-integer program-

ming issue ﬁrst (MIP), then to scheme two heuristic

algorithms and numerical search as part of a heuristic

scheme. Potential new heuristic approaches are given

in a comprehensive numerical research that is based

on information from techniques used to collect blood

samples in the real world (Elalouf et al., 2016).

The multiple knapsack optimization algorithm in-

cludes the following algorithms for example “Genetic

Algorithm, Adaptive Genetic Algorithm, Simulated

Annealing Genetic Algorithm, Adaptive Simulated

Annealing Genetic Algorithm, and Hill Climbing”

Algorithm which is also used for solving the problem

of red blood cell assignment which aims to minimize

the number of units of blood imported from outside

the system. From some of these algorithms, it is said

that Hill Climbing has a good performance in solving

these problems (Adewumi et al., 2012).

Until 2021, various optimization algorithms have

been developed to optimize the problems that occur

in the storage and distribution of blood

6 CONCLUSION

This paper discusses 45 papers from 1973 to 2021

which provide an overview of blood management

problems that are solved by various algorithms in-

cluding optimization algorithms. Several papers have

discussed the development of the optimization algo-

rithm itself to solve blood management problems.

This writing aims to ﬁnd out speciﬁc problems in

blood management problems and what algorithms are

used to solve problems in blood management. Sev-

eral papers discuss blood products, and are speciﬁc to

one of the blood products, namely platelets and red

blood cells. Platelets are widely discussed in several

studies because of the nature of platelets themselves,

that is having a short shelf life, while the nature of

the use of blood is uncertain. So that the manage-

ment of the blood itself must be optimized so that the

distribution and use of the blood becomes more opti-

mal. Optimization has many uses that can help human

activities to solve complex problems. Optimization

problems are solved such as to create optimal prod-

uct and system designs, solve mathematical problems

to get minimal costs, maximum proﬁts, optimal man-

agement and minimal errors.

There are several issues of blood management that

are discussed in several papers, namely related to

Cost production, Stock time expired, Overproduction,

Platelets have a concise shelf life, Uncertain supply

and demand for blood, Shelf life constraints, The per-

ishable nature of the blood, Minimizing operational

costs , Blood shortage and wastage due to outdat-

ing, Minimize the total cost, Inventory, Location deci-

sions, System costs and blood delivery time simulta-

neously, Time Processing, Reducing blood return and

blood loss, Maintaining sufﬁcient blood supply. With

the issue of blood management and the uncertainty of

the blood itself, this optimization algorithm is collab-

orated or compared with other algorithms. The Multi-

Objective Gray Wolf Optimizer is used to make deci-

sions about optimal location allocation, blood ﬂow,

inventory levels, and routes by minimizing total cost

and supply chain time. The particle swarm optimiza-

tion algorithm, whose results show the ability to min-

imize the import of blood units while producing no

waste. The vendor-managed inventory routing prob-

lem (VMIRP) is a method of balancing supply and de-

mand in order to reduce operational costs. It has been

discovered that using this concept, the VMIRP con-

cept can reduce the operational costs of the blood sup-

ply chain. To solve the problem of perishable blood,

the Genetic Sorting II (NSGA-II) algorithm is used.

Bounded objective function, robust optimization, and

Lagrangian relaxation to solve The uncertain demand

for blood products has also been investigated and

solved using a multi-objective mixed integer mathe-

matical programming model. To solve the problem,

a multi-objective stochastic integer linear program-

ming model is used, along with a new combination

of the Average Approximation and the Augmented

Epsilon-Constraint algorithm. Uncertainty is caused

by stochastic demand, blood type compatibility, blood

availability, and blood group proportions. Symbiotic

organisms search, genetic algorithms search, and sim-

ulated annealing algorithms search are used to solve

to identify the optimal routing for each blood group.

Hill Climbing was used to solve the problem of re-

Management Blood Using Optimization Algorithm: A State of the Art Literature Review

115

ducing the number of units of blood imported from

outside the system.

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