 An efficient optimization procedure for location-inventory problems with (S-1, S) policy and retrial demandsFong-Fan Wang Mathematics and Computers in Simulation (MATCOM), 2023, vol. 206, issue C, 664-688 Abstract: In this research, we used an easy and efficient computation procedure for deriving performance measures of (S-1, S) inventory problems with M/M/c replenishment under a retrial demand scenario. We prove some properties of the studied problem and also under back-ordered demands for comparison. We apply our method to a capacity design problem and a location-inventory design problem. For both problems, we used our method combined with direct search and genetic algorithm (GA) for optimization and compare with matrix geometric method (MGM) based evaluation and other optimization methods, including enumeration and FICO Xpress Mosel. Numerical examples show our method is about ten times more efficient than MGM-based evaluation and outperforms the other optimization methods. To find if the solution can be improved, we compare GA with other meta-heuristics, including simulated annealing, particle swarm optimization, and ant colony optimization. Finally, a sensitivity study for the location-inventory design problem is investigated. Keywords: Base stock; Retrial demand; Capacity design; Location-inventory; GA (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:206:y:2023:i:c:p:664-688 DOI: 10.1016/j.matcom.2022.12.010 Access Statistics for this article Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier |
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