tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. hence, integration has been proposed to decide about these problems concurrently. main problem in integration is how we can relate pro...

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 Paretooptimal s...

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 evolutionary algorithm is proposed to obtain a large set of Pareto-op...

in this paper, we considered solving approaches to flexible job shop problems. makespan is not a good evaluation criterion with overlapping in operations assumption. accordingly, in addition to makespan, we used total machine work loading time and critical machine work loading time as evaluation criteria. as overlapping in operations is a practical assumption in chemical, petrochemical, and gla...

This paper addresses the application of AI techniques in a practical OR problem , i.e. scheduling. Scheduling is a scientific domain concerning the allocation of tasks to a limited set of resources over time. The goal of scheduling is to maximize (or minimize) different optimization criteria such as the makespan (i.e. the completion time of the last operation in the schedule), the occupation ra...

Traditional energy-saving optimization of shop scheduling often separates the coupling relationship between a single machine and system, which not only limits potential but also leads to large deviation optimized result actual application. In practice, cutting-tool degradation during operation is inevitable, will lead increase in machining power resulting tool change disrupt rhythm production s...

Multiobjective Flexible Job Shop Scheduling Problem (MO-FJSP) is a scheduling problem used in manufacturing sectors to use energy efficiently and thriftily. The aims increase productivity reduce consumption via mathematical model. With this paper, an effective genetic algorithm proposed for MO-FJSP based on maximum completion time, total machine load, bottleneck load. solution method utilizes h...

Biogeography-based optimization (BBO) algorithm is a new kind of optimization technique based on biogeography concept. This population-based algorithm uses the idea of the migration strategy of animals or other species for solving optimization problems. In this paper, the BBO algorithm is developed for flexible job shop scheduling problem (FJSP). It means that migration operators of BBO are dev...

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) ...

The work in this paper is motivated by a recently published article which the authors developed an efficient two-stage genetic algorithm for comprehensive model of flexible job-shop scheduling problem (FJSP). In paper, we extend application to solve lot streaming FJSP while at same time expanding incorporate multiple objectives. objective function terms included our current are minimization (1)...