Job-shop manufacturing environment requires planning of schedules for the systems of low-volume having numerous variations. For a job-shop scheduling, ‘k’ number of operations and ‘n’ number of jobs on ‘m’ number of machines processed through an assured objective function to be minimized (makespan). This paper presents a capable genetic algorithm for the job-shop scheduling problems among opera...

In view of the difficulty of obtaining the optimal solution to the multi-objective scheduling of flexible job-shop by the general genetic algorithm, this paper takes into account the shortest processing time and the balanced use of machines, and puts forward the multi-population genetic algorithm based on the multi-objective scheduling of flexible job-shop. The method attempts to minimize the l...

This paper addresses the job shop scheduling problem in the presence of machine breakdowns. In this work, we propose to exploit the advantages of data mining techniques to resolve the problem. We proposed an approach to discover a set of classification rules by using historic scheduling data. Intelligent decisions are then made in real time based on this constructed rules to assign the correspo...

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...

For the Multi-Objective Flexible Job Shop Scheduling Problems (MOFJSSP), various optimization models have been designed. In the first part of the research (published in no. 2/2012) we presented the multi-sort production systems, the theoretical aspects of MOFJSSP framework, a specific real JSS process in drugs industry based on over 600 tasks to be optimally scheduled (used as a case study for ...

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...

A meta-heuristic approach for solving the flexible job-shop scheduling problem (FJSP) is presented in this study. This problem consists of two sub-problems, the routing problem and the sequencing problem and is among the hardest combinatorial optimization problems. We propose a Evolutionary Algorithm (EA) for the FJSP. Our algorithm uses several different rules for generating the initial popula...

Scheduling for the flexible job shop is very important in the fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution to this problem in medium and actual size problems with traditional optimization approaches owing to the high computational complexity. In this paper, dynamic scheduling in flexible job shop is considered. The...

in this paper, an exact geometric algorithm is presented for solving two-job sequencing and scheduling problems in flexible flow shop and job shop environments while the resources are (un)available in some time periods and processors (un)availability is the same in all work centers. this study seems utterly new and it is applicable to any performance measure based on the completion time. the in...