A modified adaptive large neighbourhood search for a vehicle routing problem with flexible time window

2021 ◽  
Vol 8 (4) ◽  
pp. 716-725
Author(s):  
F. Labdiad ◽  
◽  
M. Nasri ◽  
I. Hafidi ◽  
H. Khalfi ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Window ◽  
Time Windows ◽  
Routing Problem ◽  
Real World Application ◽  
Neighbourhood Search ◽  
Large Neighbourhood ◽  
Adaptive Large Neighbourhood Search ◽  
Large Neighbourhood Search

Vehicle routing problems are widely available in real world application. In this paper, we tackle the resolution of a specific variant of the problem called in the literature vehicle routing problem with flexible time windows (VRPFlexTW), when the solution has to obey several other constraints, such as the consideration of travel, service, and waiting time together with time-window restrictions. There are proposed two modified versions of the Multi-objective Adaptive Large Neighbourhood Search (MOALNS). The MOALNS approach and its different components are described. Also it is listed a computational comparison between the MOALNS versions and the Ant colony optimiser (ACO) on a few instances of the VRPFlexTW.

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.

Efficient Golden-Ball Algorithm Based Clustering to solve the Multi-Depot VRP With Time Windows

2018 ◽  
Vol 9 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Lahcene Guezouli ◽  
Mohamed Bensakhria ◽  
Samir Abdelhamid
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Clustering Algorithm ◽  
Optimization Problems ◽  
Time Window ◽  
Time Windows ◽  
Routing Problem ◽  
Combinatorial Optimization Problems ◽  
Acceptable Quality ◽  
Golden Ball

In this article, the authors propose a decision support system which aims to optimize the classical Capacitated Vehicle Routing Problem by considering the existence of multiple available depots and a time window which must not be violated, that they call the Multi-Depot Vehicle Routing Problem with Time Window (MDVRPTW), and with respecting a set of criteria including: schedules requests from clients, the capacity of vehicles. The authors solve this problem by proposing a recently published technique based on soccer concepts, called Golden Ball (GB), with different solution representation from the original one, this technique was designed to solve combinatorial optimization problems, and by embedding a clustering algorithm. Computational results have shown that the approach produces acceptable quality solutions compared to the best previous results in similar problem in terms of generated solutions and processing time. Experimental results prove that the proposed Golden Ball algorithm is efficient and effective to solve the MDVRPTW problem.

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