New Meta-heuristics for the Resource-constrained Project Scheduling Problem

• Main Authors: LIM, Andrew, MA, Hong, RODRIGUES, Brian, TAN, Sun Teck, XIAO, Fei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Resource-constrained project scheduling problem; Meta-heuristics; Genetic algorithms; Operations and Supply Chain Management
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/3803; https://doi.org/10.1007/s10696-011-9133-0
• Institution: Singapore Management University

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.