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

  • Construction Management
  • Published:
KSCE Journal of Civil Engineering Aims and scope

Abstract

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.

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  1. Istanbul Beykent University, Faculty of Engineering and Architecture, Civil Engineering Dept., Sariyer, 34396, Istanbul, Turkey

    Y. Cengiz Toklu

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Toklu, Y.C. Application of Big Bang - Big Crunch Optimization to Resource Constrained Scheduling Problems. KSCE J Civ Eng 22, 4760–4770 (2018). https://doi.org/10.1007/s12205-017-1549-y

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