Considering the standard particle swarm optimization (PSO) has the shortcomings of low convergence precision in job shop scheduling problems, the job shop scheduling solution is presented based on improved particle swarm optimization (A-PSO). In this paper, the basic theory of A-PSO is described. Also, the coding and the selection of parameters as well as the decoding of A-PSO are studied. It u...

The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the propos...

Dynamic job shop scheduling that considers random job arrivals and machine breakdowns is studied in this paper. Considering an event driven policy rescheduling, is triggered in response to dynamic events by variable neighborhood search (VNS). A trained artificial neural network (ANN) updates parameters of VNS at any rescheduling point. Also, a multi-objective performance measure is applied as o...

In this research we used bio-inspired metaheuristics, as artificial immune systems and ant colony algorithms that are based on a number of characteristics and behaviors of living things that are interesting in the computer science area. This paper presents an evaluation of bio-inspired solutions to combinatorial optimization problem, called the Job Shop Scheduling or planning work, in a simple ...

In our recent research, we showed results of the comparative study on effects of using several kinds of scheduling evaluation criteria as the fitness function of a genetic algorithm for job-shop scheduling. From these results, we obtained that the idle time criterion sometimes can provide a good makespan-minimizing schedule for a job-shop scheduling problem. In this paper, according to the abov...

Dynamic flexible job shop scheduling problems has been one of the important and strongly NP-hard problem of manufacturing systems for many years. Most of the proposed algorithms are based on priority rules; By using these rules, the arrived jobs go to a long queue of waited jobs and sometimes it takes a long time for a job to be processed. In this paper a new approach, integrating of priority r...

The assumption of classical shop scheduling problems that each job visits each machine only once (Baker, 1974) is often violated in practice. A new type of manufacturing shop, the reentrant shop has recently attracted attention. The basic characteristic of a re-entrant shop is that a job visits certain machines more than once. For example, in semiconductor manufacturing, consequently, each wafe...

Flexible Job Shop Problem (FJSP) is an extension of classical Job Shop Problem (JSP). The FJSP extends the routing flexibility of the JSP, i.e assigning machine to an operation. Thus it makes it more difficult than the JSP. In this study, Cooperative Coevolutionary Genetic Algorithm (CCGA) is presented to solve the FJSP. Makespan (time needed to complete all jobs) is used as the performance eva...

Job shop scheduling problems occurs in automobile industry, aerospace industry, printing industry, and chemical industry. Job shop scheduling problems are real world and complex. The present work assesses the effect of change in setup times levels on make span, maximum flow time and maximum tardiness measures. The model of the job shop is developed in PROMODEL simulation software. Three levels ...

In this paper we study specially structured two stage flow shop scheduling problem with jobs in a string of disjoint job blocks having sequence independent setup times separated from processing times each associated with their respective probabilities including job weightage. In flow shop scheduling optimization of elapsed time may not always result in optimization of utilization time. Here, th...