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The problem with flexible job planning (FJSP) is a modification o f the classic job booking problem. This paper deals with the problem o f flexible job deployment and processing o f operations on one machine from a set o f alternative machines. The problem o f deploying flexible jobs in real time is one o f a group o f difficult NP problems (Non-deterministic polynomial time). The motive o f this paper is to show the application o f meta-heuristic algorithms on the example of flexible job schedules and present the appropriate method to future studies. To solve this problem, two meta-heuristic algorithms were used: Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC). The aim o f the paper is to achieve the speed o f the conversion solution in a series o f iterations, minimizing the total time o f deployment of jobs on an alternative set of machines, as well as minimizing the total schedule time. The problem o f deploying flexible jobs has great application, and with this test we propose an algorithm for solving this problem.

Metaheuristic algorithms for the flexible job-shop scheduling problem