Research On Flexible Scheduling Problems Based On Artificial Bee Colony Algorithm

As a class of typically complex scheduling problem, flexible schedulingproblem has a strong application background while the solving complexity isvery large. As a novel intelligent algorithm, artificial bee colony (ABC)algorithm has received intensive interest due to its simple mechanism and fewparameters, while its research on the flexible scheduling problem is relativelyrare. Focusing on two typical flexible scheduling problems, i.e., flexible jobshop scheduling problem (FJSP) and flexible flow shop scheduling problem(FFSP), this dissertation carries out research on the design of ABC algorithmsand designs the corresponding simulation software. In addition to the detailedsurvey on flexible scheduling and ABC algorithms, the main research work ofthis dissertation is summarized as follows:(1) Aiming at FJSP with the criterion to minimize makespan, we proposean artificial bee colony algorithm combining with the local search based oncritical path. Via the local search based on critical path at the onlooker beephase and the updating mechanism of population with random search at thescout bee phase, local exploitation and global exploration capalities areenhanced.(2) Aiming at the multi-objective FJSP, we use a Pareto archive set tosave the non-dominated solutions and to participate in crossover at theonlooker bee phase, and design a sorting strategy for population based onnon-dominated sorting and crowding distance, and propose a Pareto-basedartificial bee colony algorithm.(3) Aiming at the fuzzy FSJP, we use fuzzy number to calculate scheduleobjective and to compare solutions, and design a crossover operator based onthe Best-so-far solution at the onlooker bee phase, and design a populationupdating mechanism at the scout bee phase, and use the local search strategybased on variable neighbouring search, and finally propose a Best-so-far artificial bee colony (B-ABC) algorithm.(4) Aiming at the hybrid flow-shop scheduling problem with unrelatedparallel machine (HFSP-UPM), we apply multiple local searches according tothe characteristics of the problem to enrich the searching behaviour, anddevelop an artificial bee colony algorithm based on permutation encoding.(5) With the background of the textile manufacturing, we design thecorresponding simulation demo software based on ABC algorithm for FFSP.A large number of computational tests and comparisons to the typicalexisting algorithms demonstrate the effectiveness of the proposed algorithms.We also investigate the effect of parameter setting on the algorithms by usingdesign of experiment.