Tour route planning multimedia system with particle swarm optimization designed

摘要

This work suggests an adaptive tour route planning multimedia system designed to meet the needs of different tourists. Tour route planning is a `traveling salesman problem' (TSP) type problem. TSP is an example of a combinatorial optimization problem and is known as NP-hard. As studied by many researchers exact, heuristic (approximation) and meta-heuristic algorithms are usually applied for NP problems. A promising meta-heuristic algorithm is proposed to solve the tour route planning problems which involves minimization of total traveling time, total travel expenses or the combined total traveling time and expenses. Moreover, a simple exchange local search heuristic is also applied to increase the exploitation (intensification) competence of the scheme. Restated, finding out the optimal planned tour using particle swarm optimization and increasing performance by exchange heuristic scheme is suggested. Simulation results indicate the PSO with exchange heuristic designed provides a promising strategy, and is efficient for solving tour route planning problems.