Variable neighborhood search algorithm for the green vehicle routing problem (original) (raw)
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A variable neighborhood search algorithm for the vehicle routing problem with multiple trips
Electronic Notes in Discrete Mathematics, 2015
The vehicle routing problem with multiple trips (V RP MT) is a variants of the standard (V RP), where each vehicle can be used more than once during the working period. For this NP-Hard problem, we propose a variable neighborhood search Algorithm in which four neighborhood structure are designed to find the planning of trips. The algorithm was tested over a set of benchmark problems and the obtained solutions were compared with five previously proposed algorithms. Encouraging results are obtained.
A variable neighbourhood search algorithm for the open vehicle routing problem
European Journal of Operational Research, 2009
In the open vehicle routing problem (OVRP), the objective is to minimise the number of vehicles and then minimise the total distance (or time) travelled. Each route starts at the depot and ends at a customer, visiting a number of customers, each once, en route, without returning to the depot. The demand of each customer must be completely fulfilled by a single vehicle. The total demand serviced by each vehicle must not exceed vehicle capacity. Additionally, in one variant of the problem, the travel time of each vehicle should not ...
Modelling and Analysis of a Green Vehicle Routing Problem
2014
The classical vehicle routing problems are designed for distance or cost reduction. The routes generated by the model will be insensitive towards the environmental impact. In this work, a green vehicle routing problem is addressed. A metaheuristic algorithm combining an Ant Colony Optimization algorithm with a Variable Neighbourhood Search algorithm is developed to solve the problem. The hybrid heuristic will search the solution space for the routing strategy, that minimizes the total supply chain cost which comprises of economic as well as emission cost. For consistency of solutions and solution convergence, the algorithm is tested on randomly generated problem instances.
An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
Computers & Operations Research, 2007
In this paper, we present an efficient variable neighborhood search heuristic for the capacitated vehicle routing problem. The objective is to design least cost routes for a fleet of identically capacitated vehicles to service geographically scattered customers with known demands. The variable neighborhood search procedure is used to guide a set of standard improvement heuristics. In addition, a strategy reminiscent of the guided local search metaheuristic is used to help escape local minima. The developed solution method is specifically aimed at solving very large scale real-life vehicle routing problems. To speed up the method and cut down memory usage, new implementation concepts are used. Computational experiments on 32 existing large scale benchmarks, as well as on 20 new very large scale problem instances, demonstrate that the proposed method is fast, competitive and able to find high-quality solutions for problem instances with up to 20,000 customers within reasonable CPU times. ᭧
The Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations
Computers & Operations Research
In this paper, we propose a metaheuristic approach for efficiently solving the Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations (G-VRP-CAFS). The G-VRP-CAFS, a variant of the traditional G-VRP, aims at routing a fleet of Alternative Fuel Vehicles (AFVs), based at a common depot, in order to serve a set of customers, minimizing the total travel distance. Due to the limited autonomy of the AFVs, some stops at Alternative Fuel Stations (AFSs) may be necessary during each trip. Unlike the G-VRP, in the G-VRP-CAFS, the AFS capacity, in terms of fueling pumps that are simultaneously available, is realistically assumed limited. For such a problem, we design an Iterated Local Search algorithm, in order to obtain good quality solutions in reasonable amount of time also on real-life alike case studies. Preliminary results, carried out on a set of benchmark instances taken from the literature, are promising.
IAEME PUBLICATON, 2020
In this paper we address a new variant of the full truck load routing problem (FTVRP) arising in the liquefied petroleum gas (LPG) industry. The objective consists of determining a schedule of daily supply which minimizes the gas transportation cost and the additional purchase costs. First, we formulate the problem as a mixed-integer linear programming model. Then, a variable neighborhood search (VNS) metaheuristic is proposed to speed up the solution procedure and to generate good feasible solutions. In the proposed VNS, The initial solution is generated using a Greedy Algorithm by selecting the most beneficial nodes. Moreover, the developed local search is based on two different mechanisms: improving solution based on the transportation cost and based on the additional purchasing cost. A set of real datasets is selected in a way that reflects the real-life company situation and used to assess the performance of the proposed VNS. Computational results of large-scale test instances show that the proposed VNS performs well and can be efficiently used to solve the problem
A Green Vehicle Routing Problem
Transportation Research Part E: Logistics and Transportation Review, 2012
A Green Vehicle Routing Problem (G-VRP) is formulated and solution techniques are developed to aid organizations with alternative fuel-powered vehicle fleets in overcoming difficulties that exist as a result of limited vehicle driving range in conjunction with limited refueling infrastructure. The G-VRP is formulated as a mixed integer linear program. Two construction heuristics, the Modified Clarke and Wright Savings heuristic and the Density-Based Clustering Algorithm, and a customized improvement technique, are developed. Results of numerical experiments show that the heuristics perform well. Moreover, problem feasibility depends on customer and station location configurations. Implications of technology adoption on operations are discussed.
2022
This paper addresses the Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery (EVRP-SPD), in which electric vehicles (EVs) simultaneously deliver goods to and pick up goods from customers. Due to the limited battery capacity of EVs, their range is shorter than that of internal combustion vehicles. In the EVRP, in addition to the depot and the customers, there are also charging stations (CS) because EVs need to be charged when their battery is empty. The problem is formulated as an integer linear model, and an efficient solution is proposed to minimize the total distance traveled. To create a feasible initial solution, Clarke and Wright’s savings algorithm is used. Several variants of variable neighborhood search are tested, and the reduced-variable neighborhood search algorithm is used to find the best solution in a reasonable time. Computer experiments are performed with benchmark instances to evaluate the effectiveness of our approach in terms of solution quality and time. The obtained results show that the proposed method can achieve efficient solutions in terms of solution quality and time in all benchmark instances.
Optimizing Green Vehicle Routing Problem-A Real Case Study
European J. of Industrial Engineering
The optimisation of distribution activities in the logistics scheme of various companies, long time based on economic objectives, is widening today to integrate environmental concerns. This paper addresses the fuel consumption minimisation problem for one variant of the green VRP which is the VRP with fuel consumption rate (FCVRP) and considers load and distance as two main factors affecting fuel consumption. The problem is classified as NP-hard, hence, we propose to solve it by an iterated local search meta-heuristic (ILSFC-SP) starting with a heuristic approach that is based on mathematical programming and generates solutions by CPLEX. In order to test its performance, ILSFC-SP was first applied on benchmark instances to minimise fuel consumption as well as travelled distance and compared with the literature where it proved its efficacy, then, it was applied to a real-world application in Tunisia where it suggested operational solutions reducing considerably the fuel costs. [
Optimising green vehicle routing problem - a real case study
European J. of Industrial Engineering
The optimisation of distribution activities in the logistics scheme of various companies, long time based on economic objectives, is widening today to integrate environmental concerns. This paper addresses the fuel consumption minimisation problem for one variant of the green VRP which is the VRP with fuel consumption rate (FCVRP) and considers load and distance as two main factors affecting fuel consumption. The problem is classified as NP-hard, hence, we propose to solve it by an iterated local search meta-heuristic (ILSFC-SP) starting with a heuristic approach that is based on mathematical programming and generates solutions by CPLEX. In order to test its performance, ILSFC-SP was first applied on benchmark instances to minimise fuel consumption as well as travelled distance and compared with the literature where it proved its efficacy, then, it was applied to a real-world application in Tunisia where it suggested operational solutions reducing considerably the fuel costs. [