The shifting bottleneck procedure for job shop scheduling
Management Science
An algorithm for solving the job-shop problem
Management Science
A practical use of Jackson's preemptive schedule for solving the job shop problem
Annals of Operations Research
A branch and bound algorithm for the job-shop scheduling problem
Discrete Applied Mathematics - Special volume: viewpoints on optimization
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
Evolution based learning in a job shop scheduling environment
Computers and Operations Research - Special issue on genetic algorithms
A fast taboo search algorithm for the job shop problem
Management Science
An effective hybrid optimization strategy for job-shop scheduling problems
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parallel GRASP with path-relinking for job shop scheduling
Parallel Computing - Special issue: Parallel computing in numerical optimization
A hybrid particle swarm optimization for job shop scheduling problem
Computers and Industrial Engineering
A very fast TS/SA algorithm for the job shop scheduling problem
Computers and Operations Research
Computers and Operations Research
A random key based genetic algorithm for the resource constrained project scheduling problem
Computers and Operations Research
Project scheduling using a competitive genetic algorithm
SMO'08 Proceedings of the 8th conference on Simulation, modelling and optimization
An optimization approach for the job shop scheduling problem
MATH'09 Proceedings of the 14th WSEAS International Conference on Applied mathematics
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This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.