Review on unrelated parallel machine scheduling problem with additional resources

• Main Authors: Abed, Munther H., Mohd Nizam, Mohmad Kahar
• Format: Article
• Language: English
• Published: College of Education, Al-Iraqia University 2023
• Subjects: QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/37799/1/Review%20on%20unrelated%20parallel%20machine%20scheduling%20problem.pdf; http://umpir.ump.edu.my/id/eprint/37799/; https://doi.org/10.52866/ijcsm.2023.02.02.020; https://doi.org/10.52866/ijcsm.2023.02.02.020
• Institution: Universiti Malaysia Pahang

This study deals with an unrelated parallel machine scheduling problem with additional resources (UPMR). That is one of the important sub-problems in the scheduling. UPMR consists of scheduling a set of jobs on unrelated machines. In addition to that, a number of one or more additional resources are needed. UPMR is very important and its importance comes from the wealth of applications; they are applicable to engineering and scientific situations and manufacturing systems such as industrial robots, nurses, machine operators, bus drivers, tools, assembly plant machines, fixtures, pallets, electricity, mechanics, dies, automated guided vehicles, fuel, and more. The importance also comes from the concern about the limitation of resources that are dedicated for the production process. Therefore, researchers and decision makers are still working on UPMR problem to get an optimum schedule for all instances which have not been obtained to this day. The optimum schedule is able to increase the profits and decrease the costs whilst satisfying the customers’ needs. This research aims to review and discuss studies related to unrelated parallel machines and additional resources. Overall, the review demonstrates the criticality of resolving the UPMR problem. Metaheuristic techniques exhibit significant effectiveness in generating results and surpassing other algorithms. Nevertheless, continued improvement is essential to satisfy the evolving requirements of UPMR, which are subject to operational changes based on customer demand.