Tabu search for solving personnel scheduling problem

Abstract

Personnel scheduling problem is combinatorial optimization problem which belongs to category of NP hard problems. This study presents a tabu search to laboratory personnel scheduling problem, assigning tasks to employees by satisfying organizational, personal and work regulation constraints. The main objective of this paper is to search for better solutions for given instance of laboratory personnel scheduling problem. Tabu search shows better results than genetic algorithmic approaches and backtracking approaches reported in literature. To further compare the performance of tabu search with genetic algorithmic approach, we have used ten instances created with our data generator. For simple data instances tabu search is found to be better than GA.