| L. Snyder, M.S. Daskin. A Random-Key Genetic Algorithm for the Generalized Traveling Salesman Problem. Working Paper, Department of Industrial Engineering and Management Sciences, Northwestern University, http://users.iems.nwu.edu/ lsnyder/papers/gtsp.html (2000). |
....E GTSP solutions are provided. Noon [50] has proposed several heuristics for the GTSP. The most sophisticated heuristic published to date is due to Renaud and Boctor [53] It is a generalization of the heuristic proposed in Renaud, Boctor and Laporte [54] for the classical TSP. Snyder and Daskin [59] have developed a genetic algorithm which is compared to the branch and cut algorithm of Fischetti, Salazar and Toth [19] and to the heuristics of Noon [50] and of Renaud and Boctor [53] This genetic algorithm is slightly slower than other heuristics, but competitive with the CPU times obtained ....
L. Snyder, M.S. Daskin. A Random-Key Genetic Algorithm for the Generalized Traveling Salesman Problem. Working Paper, Department of Industrial Engineering and Management Sciences, Northwestern University, http://users.iems.nwu.edu/ lsnyder/papers/gtsp.html (2000).
....a scheduling algorithm that utilizes the random keys encoding within the context of genetic algorithms RKGA to minimize the total tardiness and RKGA found better solutions than the other scheduling procedures. RKGA was proven to find an optimal solution if run long enough. Snyder and Daskin [13] introduced a method which combines a genetic algorithm with a local tour improvement heuristic to solve the generalized traveling salesman problem, which is a variation of the traveling salesman problem in which it is not necessary to visit all the nodes. 3. Approaches In this section the ....
Snyder, L.V. and M.S. Daskin. "A random-key genetic algorithm for the generalized traveling salesman problem. " Working Paper, Department of Industrial Engineering and Management Sciences, Northwestern University, 2001.
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