Tabu search for proactive multi-skilled resource-constrained project scheduling problem

This paper addresses a proactive multi-skilled resource-constrained project scheduling problem in which resources master multiple skills and can switch the skills they perform when allocated to different activities. The objective is to maximise schedule robustness by determining activity start times, resource assignments and the skills performed by assigned resources under precedence, renewable resource and deadline constraints. An integer linear programming model is first proposed to formulate the problem. To solve it efficiently, a tabu search algorithm is developed with a dedicated resource-skill-activity assignment algorithm embedded in the parallel schedule generation scheme. Two problem-specific improvement measures are further introduced to enhance initial solution quality and neighbourhood exploration, resulting in three tabu search variants. Through computational experiments conducted on randomly generated instances, the performance of the developed algorithms, the effectiveness of the improvement measures, the impact of resource flexibility on schedule robustness and the skill-switching characteristics of multi-skilled resources are analysed. The results demonstrate the effectiveness of the developed approach and show that multi-skilled resources can improve schedule robustness by providing greater flexibility in schedule generation. The proposed model and algorithm provide decision support for constructing robust baseline schedules in projects involving multi-skilled resources.