This paper proposes a Pareto-based grouping discrete harmony search algorithm (PGDHS) to solve the multi-objective flexible job shop scheduling problem (FJSP). Two objectives, namely the maximum completion time (makespan) and the mean of earliness and tardiness, are considered simultaneously. Firstly, two novel heuristics and several existing heuristics are employed to initialize the harmony me...

Flexible job-shop scheduling problem derived from the job-shop scheduling problem, and is more realistic than the job-shop scheduling problem in the manufacturing enterprise. It should be utilized with high efficiency. But it is a multi-objective optimal problem. Three minimization objectives (Maximum completion time (makespan), Total workload of machines and Workload of the critical machine) a...

Flexible job shop scheduling problem, is an extension of the classical job shop scheduling problem. In Flexible job shop scheduling problem, there are more than one machine with the same features for the same purpose. The problem can be defined as appointing the jobs to the machines (assignment) and ordering the jobs at each machine (sequencing) to serve the desired purpose. Multi-objective fle...

Abstract Multi-agent scheduling algorithm is a useful method for the flexible job shop problem (FJSP). Also, variability of target system has to be considered in that includes machine failure, setup change, etc. This study proposes combines independent learners with implicit quantile network by modeling FJSP high form multi-agent. The proposed demonstrates superior performance compared several ...

Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP), to discuss the method to deal with uncertainty in a manufacturing system. Design/methodology/approach: In this paper, condition based maintenance (CBM), a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simulta...

As environmental awareness grows, energy-aware scheduling is attracting increasing attention. Compared with traditional flexible job shop problem (FJSP), FJSP, considering sequence-dependent setup times and transportation (FJSP-SDST-T), closer to real production. In existing research, little research has focused on FJSP-SDST-T the minimization energy consumption. order make up gap, a mixed inte...

In the last 30 years, a flexible job shop scheduling problem (FJSP) has been extensively explored. Production efficiency is widely utilized objective. With rise in environmental awareness, green objectives (e.g., energy consumption) have received lot of attention. Nevertheless, consumption little Furthermore, controllable processing times (CPT) should be considered field scheduling, because the...

  In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Pareto-optima...

The flexible job-shop scheduling problem with indirect energy and time-of-use (ToU) electricity pricing (FJSP-IT) is investigated. Considering the production cost, which includes direct cost time evaluation model under ToU built. To minimize total of FJSP-IT, an approach based on a genetic algorithm Petri nets (GAPN) presented. Under this approach, are modeled net (PN) nodes, operation evaluate...

Abstract Different with the plain flexible job-shop scheduling problem (FJSP), FJSP routing flexibility is more complex and it can be deemed as integrated process planning (job shop) (IPPS) problem, where job shop two important functions are considered a whole optimized simultaneously to utilize in manufacturing system. Although, many novel meta-heuristics have been introduced address this corr...