Abstract
Modified Ant Colony Optimization Algorithm for Multiple-vehicle Traveling Salesman Problems
Highlights
Business and industry sectors are giving increasingly higher priority to transportation and distribution of goods because the oil price which determines a transportation cost is ever increasing
We measured the performance of our algorithm as well as other major algorithms on Traveling Salesman Problem (TSP) data from TSP Library (TSPLIB) [19]
For the single- vehicle TSP, the results of our algorithm were compared with those achieved by the ant system algorithm and elitist ant system (EAS)
Summary
Business and industry sectors are giving increasingly higher priority to transportation and distribution of goods because the oil price which determines a transportation cost is ever increasing. Meta-heuristic algorithms have been used successfully by manufacturers to reduce transport costs and enhance the business. Algorithms of this type generally find a satisfactory solution to problems, which are inherently nondeterministic polynomial-time hard (NP-hard), in an acceptably short time [1,2]. Meta-heuristic algorithms have been applied to Traveling Salesman Problem (TSP), a classic NP-hard problem that tries to find the shortest tour that a salesman can take to visit all of his customer sites in a single tour, with starting and end points at the same city.
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