An effective ant colony optimization algorithm for multi-objective job-shop scheduling with equal-size lot-splitting

2017 ◽  
Vol 57 ◽  
pp. 642-656 ◽  
Author(s):  
Rong-Hwa Huang ◽  
Tung-Han Yu
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Ant Colony ◽  
Equal Size ◽  
Ant Colony Optimization Algorithm ◽  
Shop Scheduling ◽  
Multi Objective ◽  
Lot Splitting

Job Shop-Scheduling Problems- Single Process

2010 ◽  
Vol 44-47 ◽  
pp. 330-334
Author(s):  
Ramezan Ali Mahdavinejad
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Ant Colony ◽  
Dispatching Rules ◽  
Scheduling Problems ◽  
Ant Colony Optimization Algorithm ◽  
Jobshop Scheduling ◽  
Single Process

In this paper, single-processors jobshop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan, i.e. total completion time, in which a simultanous presence of various kinds of ferons is allowed. The process of finding the best solution will be improved by using the suitable hybrid of priority dispatching rules. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. By solving some problems as samples (i.e. Fisher's & Thomson's problems), this algorithm is compared with the others. The results show that when the size of the problem becomes lorger, the deviation from lower limit increases, but its rate decreases with the size of the problems, so that it reaches to its limit.

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