A two-level based genetic algorithm for solving the soft-clustered vehicle routing problem

The soft-clustered vehicle routing problem (Soft-CluVRP) is a relaxation of the clustered vehicle routing problem (CluVRP), which in turn is a variant of the generalized vehicle routing problem (GVRP). The aim of the Soft-CluVRP is to look for a minimum cost group of routes starting and ending at a given depot to a set of customers partitioned into a priori defined, mutually exclusive and exhaustive clusters, satisfying the capacity constraints of the vehicles and with the supplementary property that all the customers from the same cluster have to be supplied by the same vehicle. The considered optimization problem is NP-hard, that is why we proposed a two-level based genetic algorithm in order to solve it. The computational results reported on a set of existing benchmark instances from the literature, prove that our novel solution approach provides high-quality solutions within acceptable running times.

Analisa Optimasi Rute Transportasi Antar Jemput Siswa Menggunakan Model CGVRP dan Algoritma Dijkstra di SDIT Darus Sunnah

School transportation is one of the facilities provided by the school in the process of picking up students. In the process of picking up, taking the optimal route is needed to save costs and time. The purpose of this study is to develop a model School transportation routes using the Clustered Generalized Vehicle Routing Problem (CGVRP ) model and the Dijkstra algorithm to get a more optimal route from the route that has been used. Furthermore, comparing the real distance from the shuttle transportation routes with the distance from the results of this case study using the CGVRP model and the Dijkstra algorithm. From the research results obtained by using the CGVRP model and the Djikstra algorithm which is applied to the case study of shuttle students at Darus Sunnah SDIT We found that our result has shorter distance when compared to the distance of the usual route.. The total distance on the SDIT Darus Sunnah route is 2.746.416 meters and costs Rp. 2.214.288 in a month. While the distance from the proposed route obtained 2.333.616 meters for at Rp. 1.881.478 in a month. Therefore the difference in the distance from the real route and the proposed route is 357.288 meters with a difference in cost of Rp. 332.820, - in a month.

Distribusi Batik Madura Melalui Penerapan Generalized Vehicle Routing Problem (GVRP)

Product distribution process is an effort to convey a product of consumer handlebar with a planned and programmed system. Cluster method is a grouping of the nearest market location, then analyzed the location of potential facilities through center of gravity. GVRP (Generalized Vehicle Routing Problem) is one of the algorithms in the cluster method [1]. In the GVRP describes the route determination to minimize the required distribution costs. GVRP is a generalization of VRP, so the point of the graph is partitioned into several sets of specific points, called clusters [2]. In this research, modification of GVRP model for multi-capacity vehicle case can determine the route and minimize the cost of distribution. Taken case on UD. Damai Asih for the distribution of Madura writes batik to 25 districts in East Java. From the results of running using MATLAB 7.8.0 obtained the efficiency of the distribution cost of 8.71% of the initial cost before doing the clustering based on distance and maximum capacity of the car of Rp. 6,969,480.00. After the filtering based on the distance and maximum capacity of the car obtained a cost of Rp. 6.365.500.00. The highest value of efficiency is obtained in cluster four, while the lowest efficiency value is obtained in cluster eight. The existence of cost efficiency is due to the different mileage in the clustering process.

Use of GVRP as a Model of Two Specific Real World Problems and Its Bioinspired Solution

The aim of this chapter is about the inclusion of real world scenarios, viewed as a Generalized Vehicle Routing Problem (GVRP) model problem, and treated by bio inspired algorithms in order to find optimum routing of product delivery. GVRP is the generalization of the classical Vehicle Routing Problem (VRP) that is well known NP-hard as generalized combinatorial optimization problem with a number of real world applications and a variety of different versions. Due to its complexity, large instances of VRP are hard to solve using exact methods. Thus a solution by a soft computing technique is desired. From a methodological standpoint, the chapter includes four bio inspired algorithms, ant colony optimization and firefly. From an application standpoint, several factors of the generalized vehicle routing are considered from a real world scenario.