A discussion on the paper on fuel consumption modeling by Post et al.

Akçelik, R; Biggs, D C

doi:10.1016/0191-2615(85)90048-7

Cited by 10 publications

(9 citation statements)

References 2 publications

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“…The accurate estimation of vehicle emissions is a nontrivial exercise for which a number of models have been proposed ( [15], [9]). The emissions characteristics of vehicles will differ depending on a range of factors, such as engine size, fuel type and mass.…”

Section: B Emissions Calculations Using a Drive Cycle And Fuel Consumentioning

confidence: 99%

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

Urquhart

Hart

Scott

2010

IEEE Congress on Evolutionary Computation

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An evolutionary Multi-Objective Algorithm (MOA) is used to investigate the trade-off between CO2 savings, distance and number of vehicles used in a typical vehicle routing problem with Time Windows (VRPTW). A problem set is derived containing three problems based on accurate geographical data which encapsulates the topology of streets as well as layouts and characteristics of junctions. This is combined with realistic speed-flow data associated with road-classes and a power-based instantaneous fuel consumption model to calculate CO2 emissions, taking account of drive-cycles. Results obtained using a well-known MOA with twin objectives show that it is possible to save up to 10% CO2, depending on the problem instance and ranking criterion used.

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Section: B Emissions Calculations Using a Drive Cycle And Fuel Consumentioning

confidence: 99%

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

Urquhart

Hart

Scott

2010

IEEE Congress on Evolutionary Computation

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“…Constraint (13) indicates the flow conservation. Constraints (14) and (15) ensure that each customer is visited only once by a single vehicle. Constraint (16) states that each vehicle carries no more than the vehicle capacity.…”

Section: Problem Description and Mathematical Formulationsmentioning

confidence: 99%

A Lagrangian Relaxation-Based Solution Method for a Green Vehicle Routing Problem to Minimize Greenhouse Gas Emissions

Zhou

Lee

2017

Sustainability

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Abstract:The effects of greenhouse gas (GHG) on the weather has caused ever-increasing disasters around the world. Many countries are making significant efforts to reduce GHG emissions in all industrial sectors. In this study, a green vehicle routing problem (GVRP) has been formulated as a nonlinear integer programming problem to minimize GHG emissions, considering various realistic factors that include three-dimensional customer locations, gravity, vehicle speed, vehicle operating time, vehicle capacity, rolling resistance, air density, road grade and inertia. Lagrangian relaxation has been introduced to propose a simple solution method. In contrast to traditional vehicle routing problems, the vehicle speed, vehicle weight, and road grade between two customer locations are also determined along with vehicle routes. The computational results demonstrate the effectiveness and efficiency of the proposed solution method.

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“…The calculation of estimated vehicle emissions is non-trivial exercise for which a number of approaches have been proposed. In this paper we examine two estimating techniques one based on [15] which attempts to calculate fuel consumption over each second of the journey and relate emissions produced to fuel used. The other (see section 3.4) is based on the work of [15] and assumes and average emissions rate over a road based on the probable speed of vehicles on that category of road.…”

Section: Estimating Vehicle Emissionsmentioning

confidence: 99%

“…A power based instantaneous fuel consumption model for road vehicles was proposed in [15]. The model may be described as follows:…”

Section: Emissions Calculations Using a Fuel Consumption Modelmentioning

confidence: 99%

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Using an Evolutionary Algorithm to Discover Low CO2 Tours within a Travelling Salesman Problem

Urquhart

Scott

Hart

2010

Applications of Evolutionary Computation

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Abstract. This paper examines the issues surrounding the effects of using vehicle emissions as the fitness criteria when solving routing problems using evolutionary techniques. The case-study examined is that of the Travelling Salesman Problem (TSP) based upon the road network within the City of Edinburgh, Scotland. A low cost path finding algorithm (A*) is used to build paths through the street network between delivery points. The EA is used to discover tours that utilise paths with low emissions characteristics. Two methods of estimating CO2 emissions are examined; one that utilises a fuel consumption model and applies it to an estimated drive cycle and one that applies a simplistic CO2 calculation model that focuses on average speeds over street sections. The results of these two metrics are compared with each other and with results obtained using a traditional distance metric.

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A discussion on the paper on fuel consumption modeling by Post et al.

Cited by 10 publications

References 2 publications

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

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

A Lagrangian Relaxation-Based Solution Method for a Green Vehicle Routing Problem to Minimize Greenhouse Gas Emissions

Using an Evolutionary Algorithm to Discover Low CO2 Tours within a Travelling Salesman Problem

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