Heterogeneous Location- and Pollution-Routing Problems

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Çağrı Koç

Department of Business Administration

Social Sciences University of Ankara, Turkey

Heterogeneous Location- and

Pollution-Routing Problems

The OR Society, Beale Lecture The Royal Society, London 22 February 2018

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Heterogeneous Location- and

Pollution-Routing Problems

PhD Dissertation

University of Southampton, 2015

Supervisor: Tolga Bektaş, University of Southampton Co-supervisor: Ola Jabali, Politecnico di Milano, Italy

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The Vehicle Routing

Problem

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The Heterogeneous Vehicle

Routing Problem

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The Location-Routing

Problem

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Vehicle Emissions and Fuel

Consumption

• Freight transportation contributed 17% of the total

Greenhouse Gas (GHG) emissions in the EU-27 countries (European Environment Agency, 2015).

• GHG emissions are proportional to fuel consumption.

• Fuel consumption is related to distance traveled, speed, vehicle curb weight and load, slopes, road surface,

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The Pollution-Routing

Problem

The PRP*: An extension of the classical VRP.

• It consists of routing vehicles to serve a set of customers, and of determining their speed on each route segment to minimize a function comprising fuel cost, emissions and driver costs.

*Bektaş, T., Laporte, G., 2011. The Pollution-Routing Problem. Transportation Research Part B 45, 1232-1250.

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Fuel consumption as a function of speed

• In congested cities, it is better to drive as fast as possible whereas on motorways it is better to drive more slowly.

• However, this is not always easy in practice because one has to drive at the traffic speed and slower driving means that companies will have to pay drivers for longer hours.

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Example

• Serves more than 220 countries.

• Uses a global air-and-ground network to speed up the delivery of time-sensitive shipments within two business days with a

guaranteed delivery time.

• More than 375 airports with 650 heterogeneous aircraft. • More than 48,000 heterogeneous vehicles.

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Example

• Between 2005-2012, achieved a 22% fuel efficiency improvement in the vehicle fleet by using hybrid trucks. • Aims

• to reduce vehicle emissions by 30% by 2020 on an emissions;

• to increase vehicle efficiency by 30% by 2020;

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1) Koç, Ç., Bektaş, T., Jabali, O., Laporte, G.,

``Thirty Years of Heterogeneous Vehicle Routing'',

European Journal of Operational Research 249, 1-21.

2015. ``A Hybrid Evolutionary Algorithm for Heterogeneous Fleet Vehicle Routing Problems with Time Windows'', Computers & Operations Research 64, 11-27.

``The Fleet Size and Mix Location-Routing

Problem with Time Windows: Formulations and a Heuristic Algorithm'', European Journal of

Operational Research 248, 33-51.

2014. ``The Fleet Size and Mix Pollution-Routing Problem'', Transportation Research Part B 70, 239-254.

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General Research

Contributions

• To analyze and investigate heterogeneous routing problems, • To introduce new variants involving aspects of:

• location,

• fleet composition,

• environmental externalities.

• To develop powerful metaheuristics • To derive several managerial insights.

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Context of the Methodology

• Many successful and powerful metaheuristic optimization

techniques have been developed for a variety of routing problems. • One of these includes evolutionary algorithms (EAs), i.e.,

genetic algorithms, which are inspired from evolutionary mechanisms found in nature.

• They combine good solutions to create new ones.

• Other successful optimization techniques are variations of local search algorithms, one of which is the large neighborhood

search algorithm (LNS).

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Context of the Methodology

• Adaptive large neighborhood search (ALNS), an extended

LNS heuristic, which uses a frequency determined by operators performance during the algorithm.

• EAs and ALNS are the state-of-the-art methods for the VRP and its variants.

• Our methodology is based on the combination of these two successful search paradigms.

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A Hybrid Evolutionary Algorithm for

Heterogeneous Fleet Vehicle Routing Problems

with Time Windows

Research objectives

• to review the latest developments;

• to identify the state-of-the-art in solution techniques;

• to introduce several algorithmic improvements to existing techniques;

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Contributions & findings

• A unified heuristic.

• Capable of solving four versions without any modification and using the same parameter settings.

• Combines:

• population search,

• adaptive large scale neighbourhood search. • Overall, on 360 benchmark instances:

• 75 solutions improved, • 102 solutions matched.

A Hybrid Evolutionary Algorithm for

Heterogeneous Fleet Vehicle Routing Problems

with Time Windows

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• to identify the latest developments on location-routing problems;

• to formulate the problem;

• to adapt the hybrid evolutionary algorithm for solving the problem;

The Fleet Size and Mix Location-Routing Problem

with Time Windows: Formulations and a Heuristic

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The Fleet Size and Mix Location-Routing Problem

with Time Windows: Formulations and a Heuristic

Algorithm

Contributions & findings • Developed

• several formulations strengthened with valid inequalities,

• a version of hybrid evolutionary algorithm. • Extensive computational experiments:

• with up to 100 customers and • 10 potential depots.

• For small size instances; optimality is within 0.05%.

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The Fleet Size and Mix

Pollution-Routing Problem

• to identify functions for modelling fuel consumption and CO₂ emissions for heterogeneous VRP;

• to formulate the problem;

• to adapt the hybrid evolutionary algorithm;

• to perform analyses leading to managerial insights. Contributions & findings:

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The impact of location, fleet composition

and routing on emissions in urban freight

distribution

• to investigate the combined impact of • depot location,

• fleet composition and

• routing decisions on vehicle emissions in urban freight distribution characterized by several speed limits,

• to devise a heuristic algorithm to solve the problem,

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• Formulated a new problem arising in urban settings with different

speed zones.

• Solved it using a version of the hybrid evolutionary algorithm:

The impact of location, fleet composition

and routing on emissions in urban freight

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• Several interesting managerial insights:

• The highest costs are incurred when all customers are located in the city centre,

• Preferable to locate the depots in the outermost zones, • Demonstrated the benefit of using a heterogeneous fleet, • Depot capacity utilization levels are higher than vehicle

capacity utilization levels.

The impact of location, fleet composition

and routing on emissions in urban freight

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Sunum Alanı İstenilen Şekilde Tasarlanabilir.

Yazı Tipi Büyüklüğü En Az 24 pt olmalıdır.

Çağrı Koç

[email protected]

Thank you for your attention!

The OR Society, Beale Lecture The Royal Society, London 22 February 2018