Authors:
Gustavo Macedo-Barragán
1
;
Samuel Nucamendi-Guillén
1
;
Elías Olivares-Benitez
1
and
Omar G. Rojas
2
Affiliations:
1
Universidad Panamericana, Facultad de Ingeniería, Prolongación Calzada Circunvalación Poniente 49, Zapopan, Jalisco and Mexico
;
2
Universidad Panamericana, Escuela de Ciencias Económicas y Empresariales, Prolongación Calzada Circunvalación Poniente 49, Zapopan, Jalisco, 45010 and Mexico
Keyword(s):
Batch Ordering, Heuristic, Mixed Integer Linear Programming, Lot Sizing, Multiple-product, Retail, Single Level.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Business Analytics
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Data Engineering
;
Decision Support Systems
;
Decision Support Systems, Remote Data Analysis
;
Health Engineering and Technology Applications
;
Industrial Engineering
;
Inventory Theory
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Linear Programming
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
Supply Chain Management
;
Symbolic Systems
Abstract:
This article presents a mixed integer linear programming method and a heuristic algorithm to deal with the problem of multi-period, multiple-product batch purchases, with a finite time horizon, considering delivery times, order placement costs and independent batch size for each product. The objective of this problem is to minimize the costs of placing purchase orders and inventory. This problem is motivated by its application in a marketing company that handles the sale of fashion products (footwear and accessories) through catalogs and for which excess inventory represents a major problem given the short life cycle of its products. Experimental results show that the heuristic algorithm is able to obtain feasible solutions that improve in cost by up to 37% the best integer solutions reported by the model when it reaches the time limit. To validate the efficiency of the algorithm, a real scenario was solved for a trading company, obtaining results that improve by 28% compared to the
current company’s situation. These results show that the heuristic approach is promising in terms of the quality of the solution and the computational time required.
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