Building low CO&lt;inf&gt;2&lt;/inf&gt; solutions to the vehicle routing problem with Time Windows using an evolutionary algorithm

Urquhart, Neil; Hart, Emma; Scott, Cathy

doi:10.1109/cec.2010.5586088

Cited by 12 publications

(6 citation statements)

References 11 publications

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“…al., 2014), the Green Vehicle Routing Problem (G-VRP) (Lin et al, 2014), and G-VRP solution approaches (Park and Chae, 2014). The incorporation of environmental considerations into vehicle routing problems has led to the development of three categories of routing models, depending on how emissions or energy consumption are modeled: i) time-independent emissions (or energy) minimising vehicle routing models (Peng and Wang, 2009;Fagerholt et al, 2010;Urquhart et al, 2010;Suzuki 2011;Rao and Jin, 2012), ii) time-dependent emissions minimising vehicle routing models (Palmer, 2007;Figliozzi, 2010;Jabali et al, 2012), and iii) load-dependent vehicle routing models (Bektas and Laporte, 2011;Franceschetti et al, 2013;Demir et al, 2014;Ehmke et al, 2016). In this last category, called Pollution Routing models, there are time-dependent (Franceschetti et al, 2013;Ehmke et al, 2016) and time-independent (Bektas and Laporte, 2011;Demir et al, 2014) formulations depending on whether time varying traffic conditions are taken into account on estimating emissions or not.…”

Section: Previous Related Workmentioning

confidence: 99%

An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations

Androutsopoulos

Zografos

2017

Transportation Research Part C: Emerging Technologies

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The consideration of pollution in routing decisions gives rise to a new routing framework where measures of the environmental implications are traded off with business performance measures. To address this type of routing decisions, we formulate and solve a bi-objective time, load and path-dependent vehicle routing problem with time windows (BTL-VRPTW). Τhe proposed formulation incorporates a travel time model representing realistically time varying traffic conditions. A key feature of the problem under consideration is the need to address simultaneously routing and path finding decisions. To cope with the computational burden arising from this property of the problem we propose a network reduction approach. Computational tests on the effect of the network reduction approach on determining non-dominated solutions are reported. A generic solution framework is proposed to address the BTL-VRPTW. The proposed framework combines any technique that creates capacity-feasible routes with a routing and scheduling method that aims to convert the identified routes to problem solutions. We show that transforming a set of routes to BTL-VRPTW solutions is equivalent to solving a bi-objective time dependent shortest path problem on a specially structured graph. We propose a backward label setting technique to solve the emerging problem that takes advantage of the special structure of the graph. The proposed generic solution framework is implemented by integrating the routing and scheduling method into an Ant Colony System algorithm. The accuracy of the proposed algorithm was assessed on the basis of its capability to determine minimum travel time and fuel consumption solutions. Although the computational results are encouraging, there is ample room for future research in algorithmic advances on addressing the proposed problem.

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Section: Previous Related Workmentioning

confidence: 99%

An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations

Androutsopoulos

Zografos

2017

Transportation Research Part C: Emerging Technologies

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“…They considered three traffic conditions: uncongested, somewhat congested and congested. Urquhart et al (2010) used evolutionary algorithms to solve VRPTW with CO 2 savings, distance and number of vehicles. Kuo (2010) proposed an algorithm for calculating traversed time and fuel consumption in TDVRP with regard to vehicle speed in his model.…”

Section: Literature Reviewmentioning

confidence: 99%

Measurement, evaluation and minimization of CO2, NO , and CO emissions in the open time dependent vehicle routing problem

Naderipour

Alinaghian

2016

Measurement

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In this paper, a new comprehensive model has been presented for the measurement, evaluation and minimization of CO2, NOx and CO as three important emissions (emitted from vehicles) in the open time dependent vehicle routing problem (OTDVRP). In the OTDVRP, traffic properties of congested regions like city centers are considered. Travel time between two points depends on the time of departure, and the vehicles do not come back to the depot. In some distribution companies, vehicles are rental; therefore, they do not come back to the depot from the last customer. To solve the proposed problem, an improved Particle Swarm Optimization algorithm is developed. The results show good performance in computation experiments compared to original PSO algorithm. The results of the experiments show that considering minimization, the pollutants can reduce emissions by 16% on the average compared to the classical open TDVRP. Factors causing the variation in emissions are also identified and discussed in this study.

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“…FCVRP has been extensively studied in the literature. Urquhart et al [19] focused on vehicle routing problem with time windows and studied the trade-offs between carbon dioxide savings, traveling distance, and the number of vehicles using evolutionary algorithms. The authors found out that up to 10% savings could be achieved.…”

Section: Literature Reviewmentioning

confidence: 99%

An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

Rao

Liu

Wang

2016

Applied Computational Intelligence and Soft Computing

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The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP’s computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS). TOHLS is based on a hybrid local search algorithm (HLS) that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.

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Building low CO<inf>2</inf> solutions to the vehicle routing problem with Time Windows using an evolutionary algorithm

Cited by 12 publications

References 11 publications

An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations

An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations

Measurement, evaluation and minimization of CO2, NO , and CO emissions in the open time dependent vehicle routing problem

An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

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