SimOpt SELSP

This work studies the problem of lot sizing and scheduling of multiple products on a single machine, with stochastic demand and sequence-dependent setup times, called Stochastic Economic Lot Scheduling Problem (SELSP). The present work differs from others in the literature by considering simple inventory control policies and using the simulation-optimization approach to calibrate their parameters. We consider two inventory control policies: (i) fixed cycling (First in Sequence - FIS) and (ii) dynamic scheduling based on inventory levels (Lowest Days of Supply - LDS), both combined with variable lot sizing. The problem is solved using AnyLogic simulation software and the OptQuest search engine to minimize the total inventory cost (ordering, holding and shortage costs). The experimental design included the following factors: number of items, coefficient of variation of demand, system workload, and degree of setup increment, allowing the comparison of the two control policies in different scenarios. The experiments show that dynamic scheduling (LDS) outperforms fixed cycling (FIS) in all scenarios, ranging from 0.2% to 4.6% reduction. The developed models proved to solve the problem, effectively generating reasonable solutions. Furthermore, as they are user-friendly, we believe they can be adapted, without great difficulties, to real-life scenarios of the process industry.

本研究探讨在单一机器上对多种产品进行批量大小和排程的问题，该问题涉及随机需求和序列依赖的设置时间，称为随机经济批量排程问题（SELSP）。本研究与文献中的其他研究有所不同，在于考虑了简单的库存控制策略，并采用模拟-优化方法来校准其参数。本研究考虑了两种库存控制策略：(i) 固定循环（按顺序第一 - FIS）和(ii) 基于库存水平的动态排程（最低供应天数 - LDS），两者均结合可变批量大小。该问题通过AnyLogic模拟软件和OptQuest搜索引擎来解决，以最小化总库存成本（订购、持有和缺货成本）。实验设计包括以下因素：项目数量、需求变异系数、系统工作负载和设置增量程度，允许在不同场景下比较两种控制策略。实验结果表明，动态排程（LDS）在所有场景中均优于固定循环（FIS），范围从0.2%至4.6%的成本降低。所开发的模型被证明能够解决问题，有效地生成合理的解决方案。此外，鉴于其用户友好性，我们相信它们可以轻松适应工艺行业的实际场景。