A genetic algorithm with neighborhood search for the resource-constrained project scheduling problem

A genetic algorithm with neighborhood search for the resource-constrained project scheduling problem

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Article ID: iaor201112737
Volume: 58
Issue: 2
Start Page Number: 73
End Page Number: 82
Publication Date: Mar 2011
Journal: Naval Research Logistics (NRL)
Authors: ,
Keywords: scheduling, heuristics: genetic algorithms, heuristics: local search
Abstract:

The resource-constrained project scheduling problem (RCPSP) consists of a set of non-preemptive activities that follow precedence relationship and consume resources. Under the limited amount of the resources, the objective of RCPSP is to find a schedule of the activities to minimize the project makespan. This article presents a new genetic algorithm (GA) by incorporating a local search strategy in GA operators. The local search strategy improves the efficiency of searching the solution space while keeping the randomness of the GA approach. Extensive numerical experiments show that the proposed GA with neighborhood search works well regarding solution quality and computational time compared with existing algorithms in the RCPSP literature, especially for the instances with a large number of activities.

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