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...

Flexibility in job shop scheduling is a main problem that has been considered by many of researchers in recent years.So Scheduling for the flexible job shop is very important in the field 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 approache...

This paper presents a meta-heuristic algorithm for solving a job shop scheduling problem involving both sequence dependent setup-times and the possibility of selecting alternative routes among the available machines. The proposed strategy is a variant of the Iterative Flattening Search (IFS) schema. This work provides three separate results: (1) a constraint-based solving procedure that extends...

Multi Objective Job Shop Scheduling Problem (MOJSP) is a problem for finding optimal operation sequences of some jobs according to more than one goal to achieve. The problem gets harder as its complexity increases. The development of optimization method has led many new methods to solve this problem. This paper offers Cross Entropy-Genetic Algorithm (CEGA) method to solve job shop scheduling pr...

This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach ...

In the last decade, various approximation approaches, such as dispatching rules, shifting bottleneck heuristic and local search methods, are proposed for the job shop scheduling problem. As one of the local search methods, taboo search provides a promising alternative for the job shop scheduling problem; however, it has to be tailored each time with respect to parameters for every instance in o...

The job shop scheduling problem is one of the most arduous combinatorial optimization problems. Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. This paper proposed a new effective approach based on the hybridization of the particle swarm optimization (PSO) an...

A recent adaptive algorithm, named Ant System, is introduced and used to solve the problem of job shop scheduling. The algorithm was first introduced by Dorigo, Maniezzo and Colorni in 1991 and is derived from the foraging and recruiting behaviour observed in an ant colony. It can be applied to combinatorial optimisation problems. This paper outlines the algorithm’s implementation and performan...

In the paper we discuss the influence of the route flexibility degree, the open rate of operations and the production type coefficient on makespan. The flexible job-open shop scheduling problem FJOSP (an extension of the classical job shop scheduling) is analyzed. For the analysis of the production process we used a hybrid heuristic of the GRASP (greedy randomized adaptive search procedure) wit...