Solving a new fuzzy multi-objective model for a multi-skilled manpower scheduling problem by particle swarm optimization and elite tabu search

Abstract

Manpower scheduling is a complicated problem to solve that strives to satisfy employers’ objectives and employees’ preferences as much as possible by generating fairly desirable schedules. But sometimes, objectives and preferences may not be determined precisely. This problem causes manpower scheduling takes the fuzzy nature. This paper presents a new fuzzy multi-objective mathematical model for a multi-skilled manpower scheduling problem considering imprecise target values of employers’ objectives and employees’ preferences. Hence, a fuzzy goal programming model is developed for the presented mathematical model and two fuzzy solution approaches are used to convert the fuzzy goal programming model to two single-objective models. Since the complexity of a manpower scheduling problem is NP-hard, the single-objective models are solved by two meta-heuristics, namely particle swarm optimization and elite tabu search. Eventually, the performance of the proposed algorithms is verified and the results are compared with each other to select the best schedules.