Fuzzy Optimization for Order and Production Scheduling

9500037 Luh本研究解决了基于订单的集成调度决策问题。制造企业的S交付和作业调度。安排订单交付的问题集中在何时将材料和供应品交付到制造站点以支持制造功能。作业调度的重点是确定作业在机器上的处理顺序，以及每个作业何时开始和完成，以达到某种目标。在大多数操作中，这两种形式的调度决策是相互独立的，即使一个领域的决策会影响另一个领域。由于这种关系，本研究旨在制定决策程序来整合它们。在研究中追求的多重目标包括：(1)利用拉格朗日松弛建立了确定性环境下作业车间、流水车间和混合车间集成问题的优化模型和近最优解方法；(2)利用模糊集理论扩展了不同车间模型以处理不确定性，并在拉格朗日松弛框架内发展了模糊优化技术；(3)发展了在拉格朗日松弛法的一个步骤中出现的具有大量变量的非光滑函数的无约束优化算法。考虑到传统的调度问题是众所周知的难以解决的问题，集成问题将带来额外的挑战。然而，鉴于问题的关键性质，试图描述问题以提供一些见解将有利于研究和从业者社区。如果成功地解决了这个问题，工业将在经济上受益。

9500037 Luh This research addresses the problem of integrating scheduling decisions on order.s deliveries and job scheduling in a manufacturing enterprise. The problem of scheduling order deliveries is focused on when materials and supplies are to be delivered at a manufacturing site to support the manufacturing function. Job scheduling is focused on the problem of determining the sequence in which jobs are to be processed on machines and when to start and complete each job so as to meet some objective. In most operations, these two forms of scheduling decision are independently made from one another even though decision in one area affects the other. Because of this relationship, this research aims to develop decision procedures to integrate them. The multiple objectives pursued in the research include: (1) development of optimization models and near-optimal solution methodologies for the integrated problem for job shops, flow shops, and hybrid shops in a deterministic setting by using Lagragian relaxation, (2) extension of the different shop models to handle uncertainty by using fuzzy set theory, and develop fuzzy optimization techniques within the Lagrangian relaxation framework, and (3) development of algorithms for the unconstrained optimization of nonsmooth functions with a large number of variables, which arise in one of the steps of the Lagrangian relaxation approach. Given the traditional scheduling problems are known to be notoriously hard to solve, the integrated problem will pose additional challenges to solve. However, given the critical nature of the problem, attempts to characterize the problem to provide some insight will be beneficial to the research and the practitioners community. Industries stand to benefit economically if a successful solution to the problem is developed.