Crucial Components of the PEAST Algorithm in Solving Real-World Scheduling Problems

Abstract

Abstract—A large number of metaheuristics and local search methods have been developed for combinatorial and global optimization. We present our PEAST algorithm which is capable of solving very difficult real-world scheduling problems, such as workforce scheduling, sports scheduling and school timetabling. The goal of this paper is to identify the crucial components of the PEAST algorithm. We believe that recognizing the importance of these components helps other researchers strengthen their population-based and local search methods. In Section III we present three plus one real-world scheduling problems which will be used to measure the importance of the components of the PEAST algorithm. The first problem occurs in scheduling the Finnish Major Ice Hockey League (13). The instance is derived from the 2012-2013 season for which the PEAST algorithm generated the schedule. The second problem occurs in solving the person-based multitask shift generation problem with breaks (17). The instance is derived from the actual problems solved for a Finnish contact center. The third problem occurs in rostering drivers for transport companies (18). The instance is derived from the biggest local transport company in Finland which uses the PEAST algorithm to optimize their driver rosters. The last problem is a school timetabling problem for which we refer to our earlier computational findings. Section IV reports the computational results. The results identify the crucial components of the algorithm. We believe that recognizing the importance of these components helps other researchers to strengthen their population-based and local search methods.