Abstract
In this paper, the authors have explained a time limited travelling salesman problem (TSP) where a time limit is associated with each city. The traveller must reach each city on or before the predetermined time limit (that is fixed for each city) in his/her tour. Travel cost is also a parameter for the proposed model. This time limit indicates the maximum time unit by which the traveller must reach a particular city. Here, travel cost is the objective of the problem. Moreover, total travel time is also fixed for a complete tour. This research recently introduced this time limit for each of the cities. The proposed TSP is solved by using a genetic algorithm-based method. The cyclic crossover and special mutation operations have been adapted to GA for solving the proposed TSP. To show the effectiveness of proposed algorithm, the authors have considered some benchmark instances. Then the authors redefine a few benchmark instances for the proposed TSP. Computational results with different data sets are presented.
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