A PSO-BASED SIMULATION OPTIMIZATION FOR A COLLABORATIVE PRODUCTION SCHEDULING PROBLEM.

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Bibliographic Details
Title: A PSO-BASED SIMULATION OPTIMIZATION FOR A COLLABORATIVE PRODUCTION SCHEDULING PROBLEM.
Authors: Zhang, L.1,2, Yan, Y.1 34117409@qq.com, Andleeb, F.3, Xu, J. R.4, Xu, W.1
Source: International Journal of Simulation Modelling (IJSIMM). Jun2026, Vol. 25 Issue 2, p352-362. 11p.
Subjects: Production scheduling, Particle swarm optimization, Bilevel programming, Mathematical optimization, Supply chains
Abstract: This study addresses collaborative production scheduling in a resource-constrained three-tier equipment manufacturing supply chain. A bilevel optimization model captures interactions between centralized penalty/incentive policies and decentralized operational decisions regarding equipment utilization, pricing, and quantity. A particle swarm optimization (PSO)-based procedure solves the nonlinear bilevel problem. Numerical simulations examine convergence, optimal scheduling, and parameter sensitivity. Results show scheduling performance jointly depends on equipment utilization elasticity, switching cost, working-hour adjustment price, and demand. Low switching costs and moderate elasticity raise efficiency and profit; adverse parameter combinations lead to lowperformance regimes. Properly designed penalties and incentives improve coordination, though their effectiveness hinges on operational flexibility and demand. The study offers a simulation-optimization framework for collaborative scheduling analysis in constrained equipment supply chains and supports decision-making for scheduling centres and enterprise planning. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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