scholarly journals Optimization of Vehicle Routing Problem with Time Window (VRPTW) for Food Product Distribution Using Genetics Algorithm

2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Rayandra Yala Pratama ◽  
Wayan Firdaus Mahmudy
Keyword(s):  
Genetic Algorithms ◽  
Population Size ◽  
Vehicle Routing ◽  
Mutation Rate ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Food Distribution ◽  
Genetic Operators ◽  
Routing Problem ◽  
Crossover And Mutation

Food distribution process is very important task because the product can expire during distribution and the further the distance the greater the cost. Determining the route will be more difficult if all customers have their own time to be visited. This problem is known as the Vehicle Routing Problem with Time Windows (VRPTW). VRPTW problems can be solved using genetic algorithms because genetic algorithms generate multiple solutions at once. Genetic algorithms generate chromosomes from serial numbers that represent the customer number to visit. These chromosomes are used in the calculation process together with other genetic operators such as population size, number of generations, crossover and mutation rate. The results show that the best population size is 300, 3,000 generations, the combination of crossover and mutation rate is 0.4:0.6 and the best selection method is elitist selection. Using a data test, the best parameters give a good solution that minimize the distribution route.

scholarly journals Selected Genetic Algorithms for Vehicle Routing Problem Solving

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3147
Author(s):  
Joanna Ochelska-Mierzejewska ◽  
Aneta Poniszewska-Marańda ◽  
Witold Marańda
Keyword(s):  
Genetic Algorithms ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Real Life ◽  
Economic Benefits ◽  
Added Value ◽  
Genetic Operators ◽  
Routing Problem ◽  
Starting Point

The traveling salesman problem (TSP) consists of finding the shortest way between cities, which passes through all cities and returns to the starting point, given the distance between cities. The Vehicle Routing Problem (VRP) is the issue of defining the assumptions and limitations in mapping routes for vehicles performing certain operational activities. It is a major problem in logistics transportation. In specific areas of business, where transportation can be perceived as added value to the product, it is estimated that its optimization can lower costs up to 25% in total. The economic benefits for more open markets are a key point for VRP. This paper discusses the metaheuristics usage for solving the vehicle routing problem with special attention toward Genetic Algorithms (GAs). Metaheuristic algorithms are selected to solve the vehicle routing problem, where GA is implemented as our primary metaheuristic algorithm. GA belongs to the evolutionary algorithm (EA) family, which works on a “survival of the fittest” mechanism. This paper presents the idea of implementing different genetic operators, modified for usage with the VRP, and performs experiments to determine the best combination of genetic operators for solving the VRP and to find optimal solutions for large-scale real-life examples of the VRP.

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

scholarly journals The last-mile vehicle routing problem with delivery options

OR Spectrum ◽  
2021 ◽  
Author(s):  
Christian Tilk ◽  
Katharina Olkis ◽  
Stefan Irnich
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Resource Constraints ◽  
Time Window ◽  
Time Windows ◽  
Service Level ◽  
Optimal Solutions ◽  
Routing Problem ◽  
Common Location ◽  
Delivery Options

AbstractThe ongoing rise in e-commerce comes along with an increasing number of first-time delivery failures due to the absence of the customer at the delivery location. Failed deliveries result in rework which in turn has a large impact on the carriers’ delivery cost. In the classical vehicle routing problem (VRP) with time windows, each customer request has only one location and one time window describing where and when shipments need to be delivered. In contrast, we introduce and analyze the vehicle routing problem with delivery options (VRPDO), in which some requests can be shipped to alternative locations with possibly different time windows. Furthermore, customers may prefer some delivery options. The carrier must then select, for each request, one delivery option such that the carriers’ overall cost is minimized and a given service level regarding customer preferences is achieved. Moreover, when delivery options share a common location, e.g., a locker, capacities must be respected when assigning shipments. To solve the VRPDO exactly, we present a new branch-price-and-cut algorithm. The associated pricing subproblem is a shortest-path problem with resource constraints that we solve with a bidirectional labeling algorithm on an auxiliary network. We focus on the comparison of two alternative modeling approaches for the auxiliary network and present optimal solutions for instances with up to 100 delivery options. Moreover, we provide 17 new optimal solutions for the benchmark set for the VRP with roaming delivery locations.

scholarly journals Implementasi Capacitated Vehicle Routing Problem with Time Windows dengan Pendekatan Algoritma Sweep untuk Distribusi Pengangkutan Sampah

2021 ◽  
Vol 19 (1) ◽  
pp. 1-6
Author(s):  
Dedi Sa'dudin Taptajani
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Time Windows ◽  
Nearest Neighbour ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Vehicle Routing Problem (VRP) merupakan suatu permasalahan yang berkaitan dengan bagaimana menentukan rute yang dianggap optimal dan melibatkan lebih dari satu alat angkut demi memperhatikan beberapa kendala dalam melayani sejumlah tempat layanan sesuai dengan permintaan. Salah satu varian dari VRP adalah capacitated vehicle routing problem with time window (CVRPTW) varian ini menambahkan kendala kapasitas alat angkut sebagai salah satu pertimbangan didalam mengangkut ke masing masing tujuan dan kemudian memberikan jendela waktu didalam proses pengangkutannya. Tujuan dari penulisan ini adalah menjelaskan pembentukan model dari CVRPTW untuk permasalahan rute pengangkutan sampah dari tiap rumah Sampai Ke Tempat Pembuangan Akhir, dengan pertimbangan waktu yang tersedia dan kapasitas angkut alat angkut yang tersedia, Sedangkan Penyelesaiannya yaitu dengan menggunakan pendekatan algoritma sweep. Algoritma Ini merupakan algoritma yang terdiri dari dua tahap, pada tahapan pertama yaitu clustering dari masing masing rumah dan tahap selanjurtnya yaitu membentuk rute pengiriman untuk masing-masing cluster dengan metode Nearest Neighbour, kemudian dilanjutkan dengan menentukan kapasitas alat angkut terhadap waktu yang diperlukan untuk menentukan kapan sampah ini akan di angkut ke tempat pembuangan akhir. Studi ini sangat penting dilakukan dalam rangka menerapkan dasar untuk memahami kemungkinan meningkatkan tingkat layanan pada proses pengangkutan sampah di tingkat desa.

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