A framework for preemptive multi-skilled project scheduling problem with time-of-use energy tariffs

Abstract

The growing importance of energy consumption has become an integral part of many decision-making processes in various organizations. In this paper, a framework is proposed for an organization where the undertaken project is implemented by multi-skilled workforce and energy tariffs depending on the time-of-use. This is a real-life situation where energy tariffs are significantly high during the peak demand compared to the one in off peak demand in order to control overloaded consumption of energy. A formulation is developed for the problem to minimize the total cost of consuming required energy. The proposed formulation is validated using several small-scale instances solved by GAMS software. To tackle large-scale instances, two intelligent meta-heuristics called electromagnetic like algorithm (EMA) and genetic algorithm (GA) are utilized. Furthermore, a comprehensive analysis is performed based on 50 test instances to evaluate the intelligence and the robustness of the employed algorithms. Finally, statistical tests are used to compare the performances of the utilized EMA and GA.