Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Film-copy deliverer problem using genetic algorithms
ICC&IE '94 Proceedings of the 17th international conference on Computers and industrial engineering
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms and Manufacturing Systems Design
Network design techniques using adapted genetic algorithms
Advances in Engineering Software
Advanced scheduling problem using constraint programming techniques in SCM environment
Computers and Industrial Engineering - Supply chain management
Dynamic Control of Genetic Algorithms Using Fuzzy Logic Techniques
Proceedings of the 5th International Conference on Genetic Algorithms
A genetic algorithm approach to a general category projectscheduling problem
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Ant colony optimization for resource-constrained project scheduling
IEEE Transactions on Evolutionary Computation
Constraining the optimization of a fuzzy logic controller using anenhanced genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hybrid genetic algorithm with adaptive local search scheme
Computers and Industrial Engineering - Special issue: Computational intelligence and information technology applications to industrial engineering selected papers from the 33 rd ICC&IE
Integrated multistage logistics network design by using hybrid evolutionary algorithm
Computers and Industrial Engineering
Hybrid genetic algorithm with adaptive local search scheme
Computers and Industrial Engineering
A new design optimization framework based on immune algorithm and Taguchi's method
Computers in Industry
Solving resource-constrained project scheduling problem as a sequence of multi-knapsack problems
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
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In this paper, we propose a hybrid genetic algorithm with fuzzy logic controller(flc-hGA)to solve the resource-constrained multiple project scheduling problem (rc-mPSP) which is well known NP-hard problem. Objectives described in this paper are to minimize total project time and to minimize total tardiness penalty. However, it is difficult to treat the rc-mPSP problems with traditional optimization techniques. The proposed new approach is based on the design of genetic operators with fuzzy logic controller (FLC) through initializing the revised serial method which outperforms the non-preemptive scheduling with precedence and resources constraints. For these rc-mPSP problems, we demonstrate that the proposed flc-hGA yields better results than conventional genetic algorithms and adaptive genetic algorithm.