Routing and scheduling in a flexible job shop by tabu search
Annals of Operations Research - Special issue on Tabu search
A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation
Computers and Industrial Engineering
Loop layout design problem in flexible manufacturing systems using genetic algorithms
Computers and Industrial Engineering - Cellular manufacturing systems: design, analysis and implementation
Computers and Industrial Engineering - Special issue on computational intelligence for industrial engineering
Computers and Industrial Engineering - 26th International conference on computers and industrial engineering
Evolutionary algorithm for advanced process planning and scheduling in a multi-plant
Computers and Industrial Engineering
An effective hybrid optimization approach for multi-objective flexible job-shop scheduling problems
Computers and Industrial Engineering
Computers and Operations Research
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
GA-based discrete dynamic programming approach for scheduling inFMS environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multicriteria meta-heuristics for AGV dispatching control based on computational intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
FMS scheduling with knowledge based genetic algorithm approach
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
A berth allocation planning problem with direct transshipment consideration
Journal of Intelligent Manufacturing
Network modeling and evolutionary optimization for scheduling in manufacturing
Journal of Intelligent Manufacturing
Multiobjective layout optimization of robotic cellular manufacturing systems
Computers and Industrial Engineering
Hybrid genetic algorithm approach for precedence-constrained sequencing problem
Computers and Industrial Engineering
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Integrated manufacturing system (IMS) is a novel manufacturing environment which has been developed for the next generation of manufacturing and processing technologies. It consists of engineering design, process planning, manufacturing, quality management, and storage and retrieval functions. Improving the decision quality in those fields give rise to complex combinatorial optimization problems, unfortunately, most of them fall into the class of NP-hard problems. Find a satisfactory solution in an acceptable time play important roles. Evolutionary techniques (ET) have turned out to be potent methods to solve such kind of optimization problems. How to adapt evolutionary technique to the IMS is very challenging but frustrating. Many efforts have been made in order to give an efficient implementation of ET to optimize the specific problems in IMS. In this paper, we address four crucial issues in IMS, including design, planning, manufacturing, and distribution. Furthermore, some hot topics in these issues are selected to demonstrate the efficiency of ET's application, such as layout design (LD) problem, flexible job-shop scheduling problem (fJSP), multistage process planning (MPP) problem, and advanced planning and scheduling (APS) problem. First, we formulate a generalized mathematic models for all those problems; several evolutionary algorithms which adapt to the problems have been proposed; some test instances based on the practical problems demonstrate the effectiveness and efficiency of our proposed approach.