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Application of Big Bang - Big Crunch Optimization to Resource Constrained Scheduling Problems

机译:Big Bang-Big Crunch优化在资源受限调度问题中的应用。

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摘要

Last decades have witnessed emergence of many different solution techniques proposed for resource constrained construction scheduling problems. High majority of these solutions involve metaheuristic techniques. Almost all of the techniques involving metaheuristic techniques are based on the search of the most convenient ordering of activities. In this study, a different approach is applied, namely, the search for the most convenient vector involving the early start days of the activities. This choice necessitated creation of two special operators called left-compression operator and right-compression operator. The use of these operators enabled determination of critical activities and critical paths for the problems with resource constraints. Analyses on example problems have indicated that for a given problem the optimum solution may not be unique, and on the other hand, there may be sub-optimal solutions where all activities are critical. The metaheuristic method used in the study is the Big Bang - Big Crunch Optimization, which could not have been applied to this problem if the vector of unknowns were considered as the ordered set of activities.
机译:过去的几十年见证了针对资源受限的施工进度问题提出的许多不同解决方案技术的出现。这些解决方案中绝大多数涉及元启发式技术。涉及元启发式技术的几乎所有技术都基于对最方便的活动排序的搜索。在这项研究中,采用了一种不同的方法,即搜索涉及活动早期开始的最方便的向量。这种选择需要创建两个特殊的运算符,分别称为left-compression运算符和right-compression运算符。使用这些运算符可以确定关键活动和资源受限问题的关键路径。对示例问题的分析表明,对于给定的问题,最佳解决方案可能不是唯一的,另一方面,在所有活动都至关重要的情况下,可能存在次优解决方案。研究中使用的元启发式方法是“大爆炸-大紧缩优化”,如果将未知向量视为活动的有序集合,则不可能将其应用于此问题。

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