AN APPLICATION OF METAHEURISTIC OPTIMIZATION ALGORITHMS FOR SOLVING THE FLEXIBLE JOB-SHOP SCHEDULING PROBLEM

Aleksandar Stanković, Goran Petrović, Žarko Ćojbašić, Danijel Marković

2020Operational Research in Engineering Sciences Theory and Applications19 citationsDOI Open Access PDF

Abstract

Abstract. The Flexible Job Planning (FJSP) problem is another planning and scheduling problem. It is a continuation of the classic problem of scheduling jobs, where each operation can be performed on different machines, while the processing time depends on the machine being used. FJSP is a difficult NP problem that consists of two sub-problems, scheduling problems and scheduling operations. The paper presents a model for solving FJSP based on meta-heuristic algorithms: Genetic algorithm (GA), Tabu search (TS) and Ant colony optimization (ACO). The efficiency of the approach in solving the aforementioned problem is reflected in the flexible search of space and the choice of dominant solutions. The results of the computation are graphically represented on the Gantt chart.

Topics & Concepts

Gantt chartJob shop schedulingMetaheuristicTabu searchMathematical optimizationComputer scienceScheduling (production processes)Flow shop schedulingNurse scheduling problemRate-monotonic schedulingDynamic priority schedulingAlgorithmScheduleMathematicsEngineeringSystems engineeringOperating systemScheduling and Optimization AlgorithmsAdvanced Manufacturing and Logistics OptimizationMetaheuristic Optimization Algorithms Research