Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
Adaptive evolutionary planner/navigator for mobile robots
IEEE Transactions on Evolutionary Computation
Fuzzy system parameters discovery by bacterial evolutionary algorithm
IEEE Transactions on Fuzzy Systems
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The paper deals with simultaneous optimization of path planning of mobile robots and flow shop scheduling problem. The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. The objective is to minimize the path length without colliding with an obstacle. On the other hand, shop scheduling problems deal with processing a given set of jobs on a given number of machines. Each operation has an associated machine on which it has to be processed for a given length of time. The problem is to minimize the overall time demand of the whole process. In this paper, we deal with two robots carrying items between the machines. Bacterial memetic algorithm is proposed for solving this combined problem. The algorithm is verified by experimental simulations and compared to classical techniques.