Improved Ant Colony Algorithm In The Application Of Flexible Job Shop Scheduling Research

To obtain the sustainable development of economic, the mode of production inmanufacturing inevitably shifts from extensive to intensive. At the same time, the marketstructure has changed from PUSH type which is Vendor-led to the PULL type which iscustomer-driven gradually. Meeting customers’ demand to a large extent become the key tosurvive even succeed in the fierce competition. Corporate products develop towards thedirection of multi-type, small batches, with different completion times and performancerequirements.Job-Shop problem is particularly important in the scheduling theory. The problemswhich Job-Shop problem solve are combinatorial optimization problems of n jobs on mmachines. This resource allocation problem to satisfy the tasks configuration andorder-constraints is NP-hard. Allocating limited resources reasonably, shortening theproduction cycle, reducing costs and meeting market demand quickly which are extremelyimportant to enterprises, are closely related to Job-Shop problem.This paper first introduces the classification, characteristics and model of Job-Shopproblem, then summarizes the various methods used in such problem. This paper alsodescribes the principle, characteristics, operation processes and key modules of ant colonyalgorithm in detail.Based on Ant Colony System (ACS) and flexible Job-Shop problem (FJSP), thispaper proposes an improved ant colony algorithm and modeling for it, then introduce thismodel by an example.Finally, Applying the model in a flexible job shop scheduling case, which includesdesign of the parameter selection,data initialization, local searching and pheromoneupdating, solving it with Matlab, and analyzing the results.