Scheduling Optimization of Manufacturing and Service Environments with Time-Lag Constraints

具有时滞约束的制造和服务环境的调度优化

• 批准号: RGPIN-2017-03743
• 负责人: Samarghandi, Hamed
• 金额: $ 3.21万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=751503
• 关键词: Scheduling; Optimization; Manufacturing; Service; Environments

The objective of this proposal is to further advance my research program in the realm of the no-wait and time-lag scheduling optimization. No-wait constraints denote that there should be no waiting time between consecutive operations of a job, which is a fundamental assumption in certain environments. Scheduling problems with time-lag constraints are a generalization of their no-wait version. Time-lag constraints force the jobs or the operations of the jobs to start or finish within a certain time window after the previous jobs or operations are completed. No-wait and time-lag constraints model situations in which a long delay between the starting time of an operation and the finish time of the previous operations is discouraged because it may damage or deteriorate the product. For example, in the food industry, many of the production procedures involve perishable products, i.e., once the food is prepared and cooked, it must undergo the chilling process before a certain amount of time is elapsed or it must be discarded. Similar constraints are in place in industries in which the risk of product contamination must be reduced. One can list biotechnology industries, for example, blood transfusion as such fields. Automated medical laboratories usually use a combination of minimal and maximal time-lags to schedule the chemical reactions correctly. Hall and Sriskandarajah [16] and Deppner [17] provide a comprehensive review of the applications of the problem.The proper objective functions to consider include minimizing the cost of production or the total processing time of the contracts in a factory; reducing the waiting time of the patients in a healthcare setting or clients in a government office. Another possibility is maximizing the utilization of the available resources. The mentioned problems are NP-hard. My research in this area during the past few years reveals that to solve the no-wait or time-lag scheduling problems to optimality using mathematical programming models, the problem instance should have less than 20 jobs. The proposed solution methods in this application progress the available literature by applying novel approaches to the scheduling problems that I have been studying for the past eight years. These methods include finding tight upper- or lower bounds for the optimal solution using semidefinite programming or Lagrangian relaxation; using decomposition techniques such as Bender's method; and conducting stochastic optimization techniques to the non-deterministic cases. The mentioned problems and solution methods are sophisticated yet fundamental and fill the gaps that currently exist in the literature. Moreover, the practicality of the defined problems and the solution methods will lead to the efficiency improvement and optimization of the Canadian and international businesses.

本文的目的是进一步推进我在无等待和时滞调度优化领域的研究计划。无等待约束是指在作业的连续操作之间不应该有等待时间，这在某些环境中是一个基本假设。带时滞约束的排序问题是无等待排序问题的推广。时滞约束迫使作业或作业的操作在前一个作业或操作完成后的某个时间窗口内开始或完成。无等待和时滞约束模型的情况下，一个操作的开始时间和前一个操作的完成时间之间的长时间延迟是不鼓励的，因为它可能会损坏或恶化的产品。例如，在食品工业中，许多生产过程涉及易腐产品，即，一旦食物被制备和烹饪，它必须在经过一定量的时间之前经历冷却过程，否则必须丢弃。在必须降低产品污染风险的行业中也存在类似的限制。可以列举生物技术行业，例如输血。自动化医学实验室通常使用最小和最大时滞的组合来正确地安排化学反应。Hall和Sriskandarajah [16]和Deppner [17]对该问题的应用进行了全面的回顾。要考虑的适当目标函数包括最小化工厂中合同的生产成本或总处理时间;减少医疗机构中患者或政府办公室中客户的等待时间。另一种可能性是最大限度地利用现有资源。上述问题都是NP难问题。我在这方面的研究，在过去的几年中，揭示了无等待或时滞调度问题的最优解数学规划模型，问题的实例应该有少于20个工作。在这个应用程序中提出的解决方案的方法进展，通过应用新的方法来调度问题，我一直在研究在过去的八年中，现有的文献。这些方法包括使用半定规划或拉格朗日松弛法找到最优解的紧上界或下界;使用Bender方法等分解技术;以及对非确定性情况进行随机优化技术。所提到的问题和解决方法是复杂的，但基本的，并填补了目前存在的文献中的空白。此外，所定义的问题和解决方法的实用性将导致加拿大和国际业务的效率提高和优化。