Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/13090
Title: An MIP-based heuristic approach to determine production lot size for capacitated single-stage production processes with stochastic demand on parallel machines
Authors: Chotayakul S.
Punyangarm V.
Keywords: Computer programming
Graph theory
Heuristic methods
Mathematical transformations
Optimal systems
Optimization
Production control
Stochastic models
Stochastic systems
Chance-constrained programming
Production lot size
Production process
Shortest path
Stochastic demand
Integer programming
Issue Date: 2017
Abstract: This paper deals with the capacitated single-stage production lot sizing and scheduling problem with multiple items, setup time, stochastic demand and unrelated parallel machines. A stochastic mixed-integer linear programming model is proposed to formulate the problem. Based on the uncertain constraints, the chance constrained programming approach is used to transform them into equivalent deterministic constraints and then obtain an optimal solution by deterministic mixed-integer linear programming model. Due to the complexity of problem, the mixed-integer programming (MIP) of the equivalence deterministic model of the capacitated single-stage production lot sizing problem with multiple items, setup time, stochastic demand and unrelated parallel machines is reformulated as a shortest path reformulation problem. The proposed algorithm is evaluated through a numerical example. Computational results show that the proposed method gives optimal or near optimal solution and have good-quality result for the test problem. © 2017 IEEE.
URI: https://ir.swu.ac.th/jspui/handle/123456789/13090
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020077748&doi=10.1109%2fICITM.2017.7917898&partnerID=40&md5=0d1bd44317b301775712c3e994571fb3
Appears in Collections:Scopus 1983-2021

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