| People | Locations | Statistics |
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| Ziakopoulos, Apostolos | Athens |
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| Vigliani, Alessandro | Turin |
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| Catani, Jacopo | Rome |
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| Statheros, Thomas | Stevenage |
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| Utriainen, Roni | Tampere |
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| Guglieri, Giorgio | Turin |
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| Martínez Sánchez, Joaquín |
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| Matos, Ana Rita |
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| Sommer, Carsten | Kassel |
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| Liu, Meiqi |
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| Pirdavani, Ali | Hasselt |
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| Lima, Pedro | Braga |
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| Turunen, Anu W. |
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| Antunes, Carlos Henggeler |
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| Krasnov, Oleg A. |
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| Lučanin, Vojkan | Belgrade |
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| Tanaskovic, Jovan |
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Braysy, Olli
in Cooperation with on an Cooperation-Score of 37%
Topics
- vehicle
- algorithm
- time window
- hill
- assessment
- customer
- survey
- optimisation
- routing
- vehicle fleet
- logistics
- travel
- travel time
- multiple use
- software
- intermodal transportation
- benchmark
- industry
- planning
- noise
- estimate
- safety
- crash
- estimating
- market
- business administration
- ground traffic
- accounting
- contracting out
- industry structure
- management information system
- logistics service provider
- evolution
- show 3 more
Publications (10/10 displayed)
- 2018Why to climb if one can jump
- 2016A Survey of Heuristics for the Vehicle Routing Problem Part I: Basic Problems and Supply Side Extensions
- 2014Chapter 12: Software Tools and Emerging Technologies for Vehicle Routing and Intermodal Transportationcitations
- 2010A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windowscitations
- 2009A well-scalable metaheuristic for the fleet size and mix vehicle routing problem with time windowscitations
- 2007Joint route planning under varying market conditionscitations
- 2007A multi-parametric evolution strategies algorithm for vehicle routing problemscitations
- 2004A multi-start local search algorithm for the vehicle routing problem with time windowscitations
- 2003A Threshold Accepting Metaheuristic for the Vehicle Routing Problem with Time Windowscitations
- 2003A Fast Evolutionary Metaheuristic for the Vehicle Routing Problem with Time Windowscitations
Places of action
document
Joint route planning under varying market conditions
Abstract
Purpose - To provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics. Design/methodology/approach - Joint route planning is a measure that companies can take to decrease the costs of their distribution activities. Essentially, this can either be achieved through horizontal cooperation or through outsourcing distribution to a logistics service provider. The synergy value is defined as the difference between distribution costs in the original situation where all entities perform their orders individually, and the costs of a system where all orders are collected and route schemes are set up simultaneously to exploit economies of scale. This paper provides estimates of synergy values, both in a constructed benchmark case and in a number of real-world cases. Findings - It turns out that synergy values of 30 per cent are achievable. Furthermore, intuition is developed on how the synergy values depend on characteristics of the distribution problem under consideration. Practical implications - The developed intuition on the nature of synergy values can help practitioners to find suitable combinations of distribution systems, since synergy values can quickly be assessed based on the characteristics of the distribution problem, without solving large and difficult vehicle routing problems. Originality/value - This paper addresses a major impediment to horizontal cooperation: estimating operational savings upfront.
Topics
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