Previous research focuses on approaches of deep reinforcement learning (DRL) to optimize diverse types the single-objective dynamic flexible job shop scheduling problem (DFJSP), e.g., energy consumption, earliness and tardiness penalty machine utilization rate, which gain many improvements in terms objective metrics comparison with metaheuristic algorithms such as GA (genetic algorithm) dispatc...

Dynamic scheduling algorithms are gaining more and more special attention for their satisfying robustness when confronted with unexpected events as well as their considerably high performance in scheduling. An organization structure for intelligent job shop scheduling based on MAS (Multiple Agents System) is put forward to achieve effective and efficient production. A hybrid multilayer agent st...

Flexible job shop schedule is very important in both fields of combinatorial optimization and production management. In this paper, a simulationmodel is presented to solve themulti-objective flexible job shop scheduling problem. The proposed model has been coded by Matlab which is a special mathematical computation language. After modeling the pending problem, the model is validated by five rep...

In the classical job shop scheduling problem (JSSP), n jobs are processed to completion on m unrelated machines. Each job requires processing on each machine exactly once. For each job, technology constraints specify a complete, distinct routing which is fixed and known in advance. Processing times are sequence-independent, fixed, and known in advance. Each machine is continuously available fro...

In this paper, scheduling problems in Flexible Manufacturing Cells (FMC) are studied. The scheduling objective is to minimize the makespan. We used a genetic algorithm (GA) for solving the optimization scheduling problem. We have developed one FMC with industrial characteristics with the objective of studying scheduling problems in these types of manufacturing systems (single machine scheduling...

Flexible job-shop scheduling problem (FJSSP) is an extension of the classical job-shop scheduling problem that allows an operation to be processed by any machine from a given set along different routes. It is very important in both fields of production management and combinatorial optimisation. This paper presents a new approach based on attribute oriented mining technique to solve the multi-ob...

Scheduling for job shop is very important in both fields of production management and combinatorial op-timization. However, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. The combination of several optimization criteria induces additional complexity and new problems. In this paper, we pro...