Vehicle routing problem with time windows (VRPTW) is one of NP-hard problem. Multi-trip is approach to solve the VRPTW that looking trip scheduling for gets best result. Even though there are various algorithms for the problem, there is opportunity to improve the existing algorithms in order gaining a better result. In this research, genetic algoritm is hybridized with simulated annealing algoritm to solve the problem. Genetic algoritm is employed to explore global search area and simulated annealing is employed to exploit local search area. Four combination types of genetic algorithm and simulated annealing (GA-SA) are tested to get the best solution. The computational experiment shows that GA-SA1 and GA-SA4 can produced the most optimal fitness average values with each value was 1.0888 and 1.0887. However GA-SA4 can found the best fitness chromosome faster than GA-SA1.
This research studied the application of multitrip vehicle routing problem with time windows (VRPTW) on the problems of the tourist routes in Banyuwangi. The problems of ordinary VRPTW has only one route to the finish line that will be targeted with specific time limits while the multi-trip VRPTW has several tourist routes and one central point as the reference point for determining the route of the tour as well as the deadline for each tour. Genetic algorithm used to solve this problem because it can overcome the problem of combinatorial effectively and efficiently, moreover it can reach solutions globally so that it can produce the optimum solution. Chromosome on the Genetic Algorithm represents the permutation of the overall tour. After decoding there are three chromosome segments created, where each segment represents a visit of tourist attractions in one day. This research provides the optimal result i.e. a solution route with the shortest commute time and a fast computing time so it is very helpful in determining the route of the tourist trips with the closest mileage based on their places to stay (centre point).
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