Comparison Analysis of Genetic Algorithm Particle Swarm Optimization and Cuckoo Search in Solving Multi-Destination Travel Cost Optimization Model

Multi-destination travel has become the main entertainment when taking long leave vacation and travel cost is the primary factor taken into consideration. To reduce customers' travel cost, we propose a multi-destination travel cost minimization model based on standard TSP. Given that the cost of transportation between two destinations and the cost of accommodation of a specific destination vary with time, we introduce the cost of transportation variable and the cost of accommodation cost. Then three meta-heuristic algorithms-genetic algorithm, particle swarm optimization and cuckoo search-are applied to solve the model. The results show that the model has strong practicability and high efficiency and cuckoo search is the best among these three heuristics to solve this model in terms of the runtime and quality of solution.