Search heuristics for resource constrained project scheduling

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We develop a search procedure for project scheduling problems with multiple resource constraints as well as precedence constraints. The procedure is applied to three popular search heuristics, simulated annealing, tabu search and genetic algorithms. In the heuristics, a solution is represented with a string of numbers each of which denotes priority of each activity. The priorities are used to select an activity for scheduling among competing ones. The search heuristics with this encoding method can always generate feasible neighbourhood solutions for a given solution. Moreover, this encoding method is very flexible in that problems with objective functions of a general functional form (such as a nonlinear function) and complex constraints can be considered without much difficulty. Results of computational tests on the performance of the search heuristics showed that the search heuristics, especially the simulated annealing and tabu search algorithms worked better than existing heuristics.
Publisher
STOCKTON PRESS
Issue Date
1996-05
Language
English
Article Type
Article
Keywords

TABU SEARCH; OPTIMIZATION; ALGORITHM; SYSTEMS; BRANCH

Citation

JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, v.47, no.5, pp.678 - 689

ISSN
0160-5682
URI
http://hdl.handle.net/10203/7609
Appears in Collection
IE-Journal Papers(저널논문)
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