The job shop scheduling problem (JSSP) has attracted much attention in the field of both information sciences and operations research. This paper considers the permutation Job shop scheduling problem with the objective of minimizing make span. Artificial Bee Colony algorithm (ABC) is one of the search heuristics used to solve global optimization problems in complex search spaces. It is observed...

In the classical job shop scheduling problem (JSSP), n jobs are processed to completion on m unrelated machines. Each job requires processing on each machine exactly once. For each job, technology constraints specify a complete, distinct routing which is fixed and known in advance. Processing times are sequence-independent, fixed, and known in advance. Each machine is continuously available fro...

We consider the problem of scheduling jobs in a hybrid job shop We use the term hybrid to indicate that we consider a lot of extensions of the classic job shop such as transportation times multiple resources and setup times The Shifting Bottleneck procedure can be generalized to deal with those extensions We test this approach for an assembly shop In this shop we study the in uence of static an...

In this paper a new neuro-genetic architecture is presented that solves a profit oriented dynamic job shop problem. In the job shop order acceptance and scheduling problem new jobs arrive continuously and because of insufficient job shop capacity, a selection has to be made among the offered jobs. The goal is to find an order acceptance policy, which is supported by a scheduling policy, that ma...

In today's world of manufacturing, cost reduction becomes one the most important issues. A successful business needs to reduce its be competitive. The programming machine is playing an role in production planning and control as a tool help manufacturers their costs maximizing use resources. problem not only limited machine, but also covers many other areas such computer information technology c...

The majority of the research using evolutionary algorithms for the Job Shop Scheduling Problem (JSSP) has studied only the static JSSP. Few evolutionary algorithms have been applied to the Dynamic Job Shop Scheduling Problem (DJSSP) which is more similar to real-world applications. We implement a hybrid genetic algorithm for solving the dynamic job shop problem. A direct chromosome representati...

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...

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...

The majority of the research using evolutionary algorithms for the Job Shop Scheduling Problem (JSSP) has studied only the static JSSP. Few evolutionary algorithms have been applied to the Dynamic Job Shop Scheduling Problem (DJSSP) which is more similar to real-world applications. We implement a hybrid genetic algorithm for solving the dynamic job shop problem. A direct chromosome representati...

This paper proposes a heuristic method based on ant colony optimization to determine the suboptimal allocation of dynamic multi-attribute dispatching rules to maximize job shop system performance (four measures were analyzed: mean flow time, max flow time, mean tardiness, and max tardiness). In order to assure high adequacy of the job shop system representation, modeling is carried out using di...