Harmony Search Method with Global Sharing Factor Based on Natural Number Coding for Vehicle Routing Problem This paper proposes an improved Harmony Search algorithm, and gives the definition of the Global Sharing Factor of the Harmony Search (HS) algorithm. In the definition, the number of creations of the HS algorithm is applied to the sharing factor and calculated. In this algorithm, the natural harmony encoding method is used to encode the initial harmony, and the total path length of all vehicles is taken as the optimization objective function. A new harmony generation strategy is proposed as follows: each tone component in an evolution is calculated separately using the new learning strategy and update strategy. In the calculation process, the tone component is judged by whether it needs to be adjusted according to the adjustment strategy. In this way, the problems of singularity and randomness of the new harmony generation strategy of basic HS are solved to improve the diversity of algorithm solutions. Then, a new Harmony Search method with Global Sharing Factor based on natural number coding and decoding for the Vehicle Routing Problem (GSFHSVRP) is proposed. The improved Global Sharing FactorHarmony SearchVehicle Routing Problem (GSFHSVRP) algorithm is applied to capacitylimited vehicle path optimization problems compared with the HS, Improved Harmony Search (IHS), Globalbest Harmony Search (GHS), and Selfadaptive Global Best Harmony Search (SGHS) algorithms. The smallscale data and Solomon examples were adopted as the experimental data. Compared with the other four algorithms, the GSFHSVRP algorithm has the shortest running time, more rapid convergence speed, and higher efficiency. In the multivehicle test, with the increase of the number of vehicles, the optimized path of the vehicle is more satisfied in relation to the actual needs of customers. The results showed that this method could effectively improve the optimization performance of the capacitylimited vehicle routing problem.

An Adaptation of the RecordtoRecord Travel Algorithm for the Cumulative Capacitated Vehicle Routing Problem The cumulative capacitated vehicle routing problem (CCVRP) is a CVRP that aims to minimize the cumulative of vehicle arrival times at every customer. This problem is suitable for the customercentric or servicecentric problem to increase the service level at customers. In the routing problem, there are many metaheuristic methods applied to solve the problem. Previous studies show that the record to record travel algorithm (RRT) has been proven to have excellent and competitive results when solving the VRP. In this paper, an RRT based algorithm is developed to address CCVRP. Several local searches (uphill and downhill moves), two general structures, and parameter values are adopted in the proposed algorithm. The dataset from previous studies is used to test the algorithm. The result obtained shows that the total cost and CPU time are competitive when compared with the published result.