Computers and Operations Research
Periodic scheduling of a transporting robot under incomplete input data: a fuzzy approach
Fuzzy Sets and Systems
A tabu search algorithm for scheduling a single robot in a job-shop environment
Discrete Applied Mathematics
Genetic algorithms with multi-parent recombination
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Single hoist cyclic scheduling with multiple tanks: a material handling solution
Computers and Operations Research - Special issue: Emerging economics
A review of machine learning in dynamic scheduling of flexible manufacturing systems
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Scheduling of coupled tasks and one-machine no-wait robotic cells
Computers and Operations Research
Computers and Operations Research
On the mean convergence time of multi-parent genetic algorithms without selection
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Binary Accelerated Particle Swarm Algorithm (BAPSA) for discrete optimization problems
Journal of Global Optimization
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In this paper, we propose a model for Flexible Job Shop Scheduling Problem (FJSSP) with transportation constraints and bounded processing times. This is a NP hard problem. Objectives are to minimize the makespan and the storage of solutions. A genetic algorithm with tabu search procedure is proposed to solve both assignment of resources and sequencing problems on each resource. In order to evaluate the proposed algorithm's efficiency, five types of instances are tested. Three of them consider sequencing problems with or without assignment of processing or/and transport resources. The fourth and fifth ones introduce bounded processing times which mainly characterize Surface Treatment Facilities (STFs). Computational results show that our model and method are efficient for solving both assignment and scheduling problems in various kinds of systems.