This study addresses the scheduling problem in remanufacturing engineering. The purpose of this paper is to model effectively to solve remanufacturing scheduling problem. The problem is modeled as flexible job-shop scheduling problem (FJSP) and is divided into two stages: scheduling and re-scheduling when new job arrives. The uncertainty in timing of returns in remanufacturing is modeled as new...

The current study presents an improved genetic algorithm(GA) for the flexible job shop scheduling problem (FJSP). The coding is divided into working sequence level and machine level and two effective crossover operators and mutation operators are designed for the generation and reduce the disruptive effects of genetic operators. The algorithm is tested on instances of 10 working sequences and 1...

Research on the Flexible Job Shop Scheduling (FJSP) problem in manufacturing process of aircraft engines has been carried out. It is found that there are real requirements such as order mandatory nodes and equipment selection current job scheduling process. Order node means some important orders must be delivered time at a certain point time, which often affects quality workshop results. In add...

Abstract In order to further reduce the carbon emission of manufacturing process in flexible job shop, a multi-objective integrated optimization model job-shop scheduling (FJSP) is proposed. A mathematics built this paper minimize makespan, total workload machines and emissions optimize method each machine characteristic, sequence allocation. Considering many parameters are interactional be opt...

Scheduling for the flexible job-shop is very important in both fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. Particle swa...

Flexible job-shop scheduling problem (FJSP) is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP) characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) for multiobjective FJSP (MO-FJSP) with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload ...

This paper addresses multiobjective flexible job-shop scheduling problem FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to mainta...

This paper proposes various lower bounds to the makespan of the flexible job shop scheduling problem (FJSP). The FJSP is known in the literature as one of the most difficult combinatorial optimisation problems (NP-hard). We will use genetic algorithms for the optimisation of this type of problems. The list of the demands is divided in two sets: the actual demand, which is considered as certain ...