An extension of the Hopfield-Tank model for solution of the Multiple Traveling Salesmen Problem. [Neural network algorithm]
Conference
·
OSTI ID:5046435
We developed an efficient neural network algorithm for solving the Multiple Traveling Salesmen Problem (MTSP). A new transformation of the N-city, M-salesmen MTSP to the standard Traveling Salesmen Problem (TSP) is introduced. The transformed problem is represented by an expanded version of Hopfield-Tank's neuromorphic city-position map with (N /plus/ M /minus/ 1)-city and a single fictitious salesman. The dynamic model associated with the problem is based on the Basic Differential Multiplier Method (BDMM). The algorithm was successfully tested on many problems with up to 30 cities and 5 salesmen. In all test cases, the algorithm always converged to valid solutions.
- Research Organization:
- Oak Ridge National Lab., TN (USA)
- DOE Contract Number:
- AC05-84OR21400
- OSTI ID:
- 5046435
- Report Number(s):
- CONF-880745-3; CONF-880745-; ON: DE88008377
- Country of Publication:
- United States
- Language:
- English
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