New Meta-heuristics for the Resource-constrained Project Scheduling Problem
In this paper, we study the resource-constrained project scheduling problem and introduce an annealing-like search heuristic which simulates the cooling process of a gas into a highly-ordered crystal. To achieve this, we develop diversification procedures that simulate the motion of high energy molecules as well as a local refinement procedure that simulates the motion of low energy molecules. We further improve the heuristic by incorporating a genetic algorithm framework. The meta-heuristic algorithms are applied to Kolisch’s PSPLIB J30, J60 and J120 RCPSP instances. Experimental results show that they are effective and are among the best performing algorithms for the RCPSP.
Resource-constrained project scheduling problem, Meta-heuristics, Genetic algorithms
Operations and Supply Chain Management
Flexible Services and Manufacturing Journal
LIM, Andrew; MA, Hong; RODRIGUES, Brian; TAN, Sun Teck; and XIAO, Fei.
New Meta-heuristics for the Resource-constrained Project Scheduling Problem. (2013). Flexible Services and Manufacturing Journal. 25, (1), 48-73. Research Collection Lee Kong Chian School Of Business.
Available at: http://ink.library.smu.edu.sg/lkcsb_research/3803