A Neurogenetic approach for the resource-constrained project scheduling problem
A Neurogenetic approach for the resource-constrained project scheduling problem
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DOI：
10.1016/j.cor.2010.01.007
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Anurag Agarwal;Selçuk Çolak;Selcuk Erenguc
中科院分区：
文献类型：
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作者：
Anurag Agarwal;Selçuk Çolak;Selcuk Erenguc
A variety of metaheuristic approaches have emerged in recent years for solving the resource-constrained project scheduling problem (RCPSP), a well-known NP-hard problem in scheduling. In this paper, we propose a Neurogenetic approach which is a hybrid of genetic algorithms (GA) and neural-network (NN) approaches. In this hybrid approach the search process relies on GA iterations for global search and on NN iterations for local search. The GA and NN search iterations are interleaved in a manner that allows NN to pick the best solution thus far from the GA pool and perform an intensification search in the solution's local neighborhood. Similarly, good solutions obtained by NN search are included in the GA population for further search using the GA iterations. Although both GA and NN approaches, independently give good solutions, we found that the hybrid approach gives better solutions than either approach independently for the same number of shared iterations. We demonstrate the effectiveness of this approach empirically on the standard benchmark problems of size J30, J60, J90 and J120 from PSPLIB.
