摘要翻译:
我们考虑了一个多地点库存系统,其中每个地点的库存选择是集中协调的。允许横向转运作为库存系统中同一梯队内的追索行动,以降低成本和提高服务水平。然而,这种转运过程通常会造成不理想的提前期。本文提出了一个多地点转运问题的多目标模型,解决了三个相互冲突的目标的优化问题:(1)总期望成本最小化,(2)期望装卸率最大化,(3)期望转运提前期最小化。我们采用一种基于强度Pareto进化算法(SPEA2)的进化多目标优化方法来逼近最优Pareto前沿。在模型参数选择较多的情况下,仿真结果显示了冲突目标之间的不同折衷。
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英文标题:
《Evolutionary multiobjective optimization of the multi-location
transshipment problem》
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作者:
Nabil Belgasmi (SOIE), Lamjed Ben Said (SOIE), Khaled Gh\'edira (SOIE)
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最新提交年份:
2011
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Artificial Intelligence 人工智能
分类描述:Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域,除了视觉、机器人、机器学习、多智能体系统以及计算和语言(自然语言处理),这些领域有独立的学科领域。特别地,包括专家系统,定理证明(尽管这可能与计算机科学中的逻辑重叠),知识表示,规划,和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类:Mathematics 数学
二级分类:Optimization and Control 优化与控制
分类描述:Operations research, linear programming, control theory, systems theory, optimal control, game theory
运筹学,线性规划,控制论,系统论,最优控制,博弈论
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英文摘要:
We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However, this transshipment process usually causes undesirable lead times. In this paper, we propose a multiobjective model of the multi-location transshipment problem which addresses optimizing three conflicting objectives: (1) minimizing the aggregate expected cost, (2) maximizing the expected fill rate, and (3) minimizing the expected transshipment lead times. We apply an evolutionary multiobjective optimization approach using the strength Pareto evolutionary algorithm (SPEA2), to approximate the optimal Pareto front. Simulation with a wide choice of model parameters shows the different trades-off between the conflicting objectives.
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PDF链接:
https://arxiv.org/pdf/1102.1536