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TBB (Thread Building Blocking) is currently a representative parallel computing platform of multi-core processors. The ant colony algorithm is used to solve combinatorial optimization problem of discrete-time systems. With the expansion of the problem scale, it often results in rapid increase of calculation. Based on TBB a parallel ant colony algorithm was researched and developed to improve the efficiency...
When trying to find approximate solutions for the Traveling Salesman Problem with heuristic optimization algorithms, the reduction of the computational time or the increase of the exploration in the search space are two important aspects. Used variable neighborhood search to solving the Traveling Salesman Problem, and improved this algorithm in initial solution's production, neighbor structure and...
Parallel implementation of ant colony optimization (ACO) can reduce the computational time obviously for the large scale combinatorial optimization problem. A novel parallel ACO algorithm is proposed in this paper, which use dynamic transition probability to enlarge the search space by stimulating more ants choosing new path at early stage of the algorithm; use new parallel strategies to improve the...
Ant colony algorithm is an efficient intelligent algorithm to solve NP hard problem. This paper presents a parallel computing solution based on General Purpose GPU (GPGPU) to solve traveling salesman problem (TSP) with max-min ant system (MMAS). The experimental result shows it is more efficient than pure CPU computing.
Inspired by the behavior of people, a new algorithm for the combinatorial optimization is proposed. This is a heuristic approach based on swarm intelligence, which is firstly introduced as the theoretical background in this paper. It is also a parallel algorithm, in which individuals of the swarm search the state space independently and simultaneously. When one encounters another in the process, they...
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