An Ant Colony Optimization Algorithm for Job Shop Scheduling Problem

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Provided by: Academy & Industry Research Collaboration Center
Topic: Software
Format: PDF
The nature has inspired several metaheuristics, outstanding among these is Ant Colony Optimization (ACO), which have proved to be very effective and efficient in problems of high complexity (NP-hard) in combinatorial optimization. This paper describes the implementation of an ACO model algorithm known as Elitist Ant System (EAS), applied to a combinatorial optimization problem called Job Shop Scheduling Problem (JSSP). The authors propose a method that seeks to reduce delays designating the operation immediately available, but considering the operations that lack little to be available and have a greater amount of pheromone.
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