A concurrent neural network algorithm for the traveling salesman problem

Conference · Thu Dec 31 23:00:00 EST 1987

OSTI ID:5271931

Toomarian, N

A binary neuromorphic data structure is used to encode the N-city Traveling Salesman Problem (TSP). In this representation the computational complexity, in terms of number of neurons, is reduced from Hopfield and Tank's 0(N/sup 2/) to 0(N log/sub 2/N). A continuous synchronous neural network algorithm in conjunction with the Lagrange multiplier, is used to solve the problem. The algorithm has been implemented on the NCUBE hypercube multiprocessor. This algorithm converges faster and has a higher probability to reach a valid tour than previously available results. 22 refs., 3 figs., 2 tabs

• Research Organization: Oak Ridge National Lab., TN (USA)
• DOE Contract Number: AC05-84OR21400
• OSTI ID: 5271931
• Report Number(s): CONF-880117-2; ON: DE88006981
• Country of Publication: United States
• Language: English

Related Subjects

551000 -- Physiological Systems
59 BASIC BIOLOGICAL SCIENCES
99 GENERAL AND MISCELLANEOUS
990210* -- Supercomputers-- (1987-1989)
ALGORITHMS
COMPUTERS
CONVERGENCE
DECISION MAKING
HYPERCUBE COMPUTERS
MATHEMATICAL LOGIC
MATHEMATICAL MODELS
NERVOUS SYSTEM
NETWORK ANALYSIS
NONLINEAR PROBLEMS
OPTIMIZATION
SYNCHRONIZATION