Abstract
Scheduling can be described as a decision-making process. It is applied in various applications, such as manufacturing, airports, and information processing systems. More so, the presence of symmetry is common in certain types of scheduling problems. There are three types of parallel machine scheduling problems (PMSP): uniform, identical, and unrelated parallel machine scheduling problems (UPMSPs). Recently, UPMSPs with setup time had attracted more attention due to its applications in different industries and services. In this study, we present an efficient method to address the UPMSPs while using a modified harris hawks optimizer (HHO). The new method, called MHHO, uses the salp swarm algorithm (SSA) as a local search for HHO in order to enhance its performance and to decrease its computation time. To test the performance of MHHO, several experiments are implemented using small and large problem instances. Moreover, the proposed method is compared to several state-of-art approaches used for UPMSPs. The MHHO shows better performance in both small and large problem cases.
Highlights
Parallel machine scheduling only has an important role not in manufacturing, but in many scheduling processes, including transport scheduling like train schedules, airport management like landing scheduling, and hospital management, such as surgery scheduling
The Modified HHO (MHHO) algorithm begins by creating random integer numbers to represent the initial solution of unrelated parallel machine scheduling problems (UPMSPs) solutions (X), whereas the solution includes a set of individuals (N) for a set of n jobs that listed to be processed over m machines
A set of the UPMSP benchmark dataset is used to assess the performance of the MHHO
Summary
Parallel machine scheduling only has an important role not in manufacturing (e.g., electronic and chemical industries), but in many scheduling processes, including transport scheduling like train schedules, airport management like landing scheduling, and hospital management, such as surgery scheduling. Symmetry has a presence in different scheduling problems [1,2]. Parallel machine scheduling can be considered as complex artificial systems that have the characteristics of randomness, multi constraint, complexity, and multi-objective, etc. Job scheduling problems are known as NP-hard problems, due to their complexity, randomness, multi-objectives, and multi-variables [3]. Machine job scheduling problems are very important and they have gained a huge influence to increase manufacturing productivity and to improve service operations.
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