Dynamic and Stochastic Job Shop Scheduling Problems Using Ant Colony Optimization Algorithm
نویسندگان
چکیده
Reactive scheduling is often been criticized for its inability to provide timely optimized and stable schedules. So far, the extant literature has focused on generating schedules that optimize shop floor efficiency. Only a few have considered optimizing both shop floor efficiency and schedule stability. This paper applies a unique selfadaptation mechanism of the ant colony optimization (ACO) algorithm to enable the reactive scheduling approach to generate better and timely stable and quality schedules for dynamic and stochastic job shop scheduling problems.
منابع مشابه
Applying Ant Colony Optimisation (ACO) algorithm to dynamic job shop scheduling problems
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