We combine genetic algorithms and case-based reasoning principles to nd optimally directed solutions to open shop scheduling and open shop rescheduling problems. Appropriate solutions to open shop scheduling problems are injected into the genetic algorithm's population to speed up and augment genetic search on a related open shop rescheduling problem. Preliminary results indicate that the combi...

This paper addresses the open shop scheduling problem. this problem, due to its complexity, is ranked in the class of NPhard problems. In this case, traditional approaches cannot reach to an optimal solution in a reasonable time. So heuristic algorithms such as simulated Annealing (SA), tabu search (TS) genetic algorithm, (GA), ant colony optimization (ACO) used to solve optimization problems s...

This paper aims to prove the efficiency of an adapted computationally intelligence-based behavior of cats called the cat swarm optimization algorithm, that solves the open shop scheduling problem, classified as NP-hard which its importance appears in several industrial and manufacturing applications. The cat swarm optimization algorithm was applied to solve some benchmark instances from the lit...

This paper represents the metaheuristics proposed for solving a class of Shop Scheduling problem. The Bacterial Foraging Optimization algorithm is featured with Ant Colony Optimization algorithm and proposed as a natural inspired computing approach to solve the Mixed Shop Scheduling problem. The Mixed Shop is the combination of Job Shop, Flow Shop and Open Shop scheduling problems. The sample i...

scheduling for job shop is very important in both fields of production management and combinatorial op-timization. however, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. the combination of several optimization criteria induces additional complexity and new problems. in this paper, we pro...

this paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. in the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). however,, two significant criteria for each schedule in stochastic models are: expectable m...

This Paper is an attempt to study two stage open shop scheduling problem in which processing time of the jobs are given. The objective of the paper is to obtain an algorithm to minimize the rental cost of the machines in two stage open shop scheduling problem under specified rental policy. A numerical illustration is given to justify the proposed algorithm.

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...

job shop scheduling problem has significant importance in many researchingfields such as production management and programming and also combinedoptimizing. job shop scheduling problem includes two sub-problems: machineassignment and sequence operation performing. in this paper combination ofparticle swarm optimization algorithm (pso) and gravitational search algorithm(gsa) have been presented f...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...