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A developed Dijkstra shortest path search algorithm is proposed through improving data structure, preprocessing to remove redundant vertices and setting the search region sequence. The average running time before and after improvement is compared and analyzed through the simulation tests. The results show that the developed Dijkstra shortest path search algorithm can improve storage efficiency and...
This paper presents a new approach for solving network routing optimization problems. In particular, the goal is to optimize the traffic in the network structured event-driven systems as well as to provide means for efficient adaptation of the system to changes in the environment-i.e. when some nodes and/or links fail. Many network routing optimization problems belong to the class of NP hard problems,...
Traveling salesman problem (TSP) is one of the most famous NP-hard problems, which has wide application background. Ant colony optimization (ACO) is a nature-inspired algorithm and taken as one of the high performance computing methods for TSP. Classical ACO algorithm like ant colony system (ACS) cannot solve TSP very well. The present paper proposes an ACO algorithm with multi-direction searching...
To solve a typical NP-hard combinatorial optimization problem-traveling salesman problem, ant colony optimization based on minimum spanning tree(MST-ACO), is presented and the performance is reported. The mechanism of MST-ACO is described from three aspects: adopting dual nearest insertion procedure to initialize the pheromone, integrating reinforcement learning through computing lowbound by 1-minimum...
To reduce further the searching complexity and memory requirement of tree-structured vector quantization (TSVQ), novel multisubspace TSVQ design algorithms and encoding techniques are proposed. The proposed multisubspace TSVQ design algorithms perform the vector quantization in the spatial domain while using specially designed subspace distortions in the transform domain as cost functions for the...
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