Scheduling optimization for FMS based on Petri net modeling and GA

Job-shop scheduling optimization design based on an improved GA

“…As the optimization is not under the constraint of restrictive condition, the genetic algorithm has been applied widely at present [9]. In this paper, an improved genetic algorithm is proposed, and the fitness function, the selection operator and the crossover operator are also improved which can be seen as follows [10].…”

“…Solving the minimum scheduling time is the research target and the genetic algorithm requires that the better solution has bigger nonnegative fitness value, so the fitness function is selected based on the two main principles [10]. One is the processing sequence principle, and the other is the minimum waiting time principle.…”

Research on the Assembly Line Scheduling of Fixed Objects for the Large Complex Products

“…Pi represents the selected probability. The individual number of every generation is M. (4) Crossover Operator The crossover operator can make the genes of the different parent individuals partially cross and transform according to some certain crossover probability in order to generate new excellent individuals [4]. We use the POX(precedence operation crossover) method.…”

“…The FT problems have become generally accepted benchmark examples which are used to test the scheduling algorithm [7], so the FT06 is used to test the proposed algorithm in the paper.…”

A Rank Based ACO Approach for Optimal Resource Allocation and Scheduling in FMS Modeled with Labelled Petri Net

“…As a mathematical tool, it is possible to set up equations of state, algebraic equations, and other mathematical models governing the behavior of the system. Various traditional optimization techniques are aggregated with different extensions of Petri Nets PN, like fuzzy logic [3], dispatching rules [4], heuristic research [5], [6], [7], [8], and meta-heuristic research [9], [10].…”