Blocking The Optimization Of Flow Shop Scheduling Methods Of Research

Blocking flow shop scheduling problem is a very important scheduling problem.Recently, many meta-heuristics have been applied to this problem. For example: Harmonysearch (HS) algorithm, Differential evolution (DE) algorithm, artificial bee colony (ABC)algorithm, Genetic algorithm (GA), Taboo search (TS) and so on. Because of theirsimplicity, fewer mathematical requirements, ease of implementation and so on, HS, DE,GA, TS and ABC algorithms have been captured much attention in academic field andengineering field. This paper studies the blocking flow shop scheduling problem based onthe harmony search algorithm and artifical bee colony algorithm as follows:1. Structure of blocking flow shop scheduling problemBlocking flow shop scheduling is different from regular flow shop scheduling sincethe flow shop has no intermediate buffers. The objective of this paper is to find minimummaximum completion time (makespan) and total flow time respectively.2. Solving blocking flow shop secheduling problem based on discrete harmony searchThe basic HS algorithm is of continuous nature, and it cannot be directly to generate afeasible job permutation for the problem considered. Therefore, we present a discrete HSalgorithm (DHS). The proposed DHS algorithm utilizes discrete job permutations torepresent harmonies. Meanwhile, the local search anad speed-up neighborhood searchmethod are presented and embedded into the HS algorithm to enhance its local searchingability and effectiveness of the algorithm.3. Solving blocking flow shop secheduling problem based on discrete artifical beecolony algorithmThe Artificial Bee Colony (ABC) algorithm was first presented by Karabogaforreal-parameter optimization. This paper adopt discrtet artificial bee colony algorithm(DABC) for the blocking flow shop (BFS) scheduling problem to minimize makespan. Thelocal search is presented and embedded into the DABC algorithm. Simulation results andcomparisons demonstrate the effectiveness and feasiblebily of the proposed algorithms.4. Solving blocking flow shop secheduling problem based on Hybrid discrete artifical bee colony algorithmArtifial bee colony algorithm simulates the foraging behavior of a bee colony andclassifies bees into three categories: employed bees, onlookers and scouts. The insertionand swap operators show the superiority to generate a neighboring the solution, thesesolutions obtained by insertion and swap operators may be trapped in the local optimum.Therefore, in this section, we adopt the estimation of the distribution algorithm to enrichthe diversity of the solution in population space.This research is partially supported by National Science Foundation of China underGrants60874075and Postdoctoral Science Foundation of China under Grants20100480897.