Proceedings in Adaptation, Learning and Optimization

This paper considers a static resource constrained multi-project scheduling problem (RCMPSP) with two lateness objectives: project lateness and portfolio lateness. To solve the RCMPSP, we have proposed an evolutionary local search heuristic that uses a variable neighborhood (ELSH-VN) approach. The heuristic is further analyzed by incorporating different priority-rules. To judge the performance of these priority rule based heuristics, an extensive simulation-based analysis has been conducted with different scenario-based schedules. For the experimental study, we have considered a standard set of 77 generated RCMPSP test instances of 20 activities. The experimental analysis indicates that the proposed heuristic is able to solve multiple projects with reasonable computational burden. The influence of the variation of resource distribution and resource contention on the algorithm’s performance for different priority rules is also analyzed and discussed.

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