Authors:
Davide Giglio
and
Massimo Paolucci
Affiliation:
University of Genova, Italy
Keyword(s):
Remanufacturing, Production Scheduling, Mixed-integer Programming Modelling, Matheuristics.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Formal Methods
;
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Planning and Scheduling
;
Production Planning, Scheduling and Control
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
An integrated manufacturing/remanufacturing system is considered in this paper with the aim of scheduling
the operations of the manufacturing plant. The system is partially closed in the sense that the raw materials,
necessary for assembling the final products, can be obtained both from an internal remanufacturing plant
(which disassembles returned products) and from external suppliers. The manufacturing system is modelled
as a flexible flow shop whose stages represent the different assembly phases leading to the final products.
In this paper, an original event-based mixed integer programming (MIP) formulation is presented, whose
objective consists of minimizing, as primary objective, the weighted number of tardy jobs and, as secondary
ones, the fixed and variable purchase costs of raw materials possibly acquired from external suppliers. Due to
the complexity of the problem, the MIP formulation can be used to solve only small instances. For this reason,
a matheuristics is proposed, w
hich consists of three interoperating mathematical programming models: the
first model assigns the jobs to the machines; the second model sequences the jobs on the machines; the third
model defines the external supplies, taking into account the component availability constraints. A preliminary
computational analysis shows the effectiveness of the proposed algorithm.
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