This work suggests an adaptive tour planning multimedia system designed to meet the tour routing needs of different tourists. Tour planning is an application of vehicle routing problem. Meanwhile, vehicle routing problem 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 routing 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 routes using particle swarm optimization (PSO) 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 routing problems. (27 refs)
