Table of Contents

Multi-Agent Systems in Logistics: A Literature and State-of-the-Art Review

Niels Lang, Erasmus University Rotterdam (EUR) - RSM Erasmus University
Hans Moonen, Erasmus University Rotterdam (EUR) - Department of Decision and Information Sciences
F. Jordan Srour, Erasmus University Rotterdam (EUR) - RSM Erasmus University
Rob A. Zuidwijk, Erasmus University Rotterdam (EUR) - RSM Erasmus University, Erasmus Research Institute of Management (ERIM) - Joint Research Institute of Rotterdam School of Management (RSM) and Erasmus School of Economics(ESE), EUR

Bullwhip and Reverse Bullwhip Effects under the Rationing Game

Ying Rong, Lehigh University - Industrial and Systems Engineering Department
Lawrence V. Snyder, Lehigh University
Zuo-Jun Max Shen, University of California, Berkeley - Department of Industrial Engineering & Operations Research (IEOR)

Greening Transportation Fleets

Sang Hoo Bae, Clark University - Department of Economics
Chung Sik Yoo, Yonsei University
Joseph Sarkis, Clark University - Graduate School of Management


LOGISTICS ABSTRACTS

"Multi-Agent Systems in Logistics: A Literature and State-of-the-Art Review" Free Download
ERIM Report Series Reference No. ERS-2008-043-LIS

NIELS LANG, Erasmus University Rotterdam (EUR) - RSM Erasmus University
HANS MOONEN, Erasmus University Rotterdam (EUR) - Department of Decision and Information Sciences
Email:
F. JORDAN SROUR, Erasmus University Rotterdam (EUR) - RSM Erasmus University
ROB A. ZUIDWIJK, Erasmus University Rotterdam (EUR) - RSM Erasmus University, Erasmus Research Institute of Management (ERIM) - Joint Research Institute of Rotterdam School of Management (RSM) and Erasmus School of Economics(ESE), EUR
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Based on a literature survey, we aim to answer our main question: How should we plan and execute logistics in supply chains that aim to meet today's requirements, and how can we support such planning and execution using IT? Today's requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements. The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today's requirements in supply chain planning and execution.

"Bullwhip and Reverse Bullwhip Effects under the Rationing Game" Free Download

YING RONG, Lehigh University - Industrial and Systems Engineering Department
Email:
LAWRENCE V. SNYDER, Lehigh University
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ZUO-JUN MAX SHEN, University of California, Berkeley - Department of Industrial Engineering & Operations Research (IEOR)
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We revisit the bullwhip effect (BWE) under the rationing game. We prove that, for a large class of supply processes, no Nash Equilibrium (NE) of the retailers' order quantities exists, and therefore the classical analysis fails in these cases. Moreover, we argue that it is not clear if and when the BWE occurs even when an NE exists. We modify the classical rationing game model slightly to derive a more tractable model, and we use this model to provide the first proof that the BWE always occurs downstream under the rationing game when the mean demand changes over time. Moreover, we also prove that the reverse bullwhip effect (RBWE) occurs upstream in the same setting. Whereas the BWE describes increased order variabiltiy upstream and is caused by demand uncertainty, the RBWE describes increased variability downstream and is caused by supply uncertainty.

We formulate an additional model in which the retailers pay a reservation payment for each unit ordered, regardless of whether it is delivered, and prove that an NE exists in this setting, regardless of how small the reservation payment is. We characterize the conditions under which the BWE and RBWE occur in this model. Finally, we provide a multi-period simulation model to explore the relationship between the [R]BWE and the cost of the supply chain under different allocation rules and capacity processes. We find that, contrary to intuition, more severe [R]BWE does not necessarily lead to higher costs.

"Greening Transportation Fleets" Free Download

SANG HOO BAE, Clark University - Department of Economics
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CHUNG SIK YOO, Yonsei University
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JOSEPH SARKIS, Clark University - Graduate School of Management
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The greening of organizational transportation fleets, especially trucks and automobiles, has gained increasing attention by companies in a variety of industrial sectors. The reasons for this concern and attention are due to regulatory and competitive pressures, but also increasing costs of fossil-fuels. Surprisingly the amount of research and modeling for fleet management overall has been rather limited, with the focus on managing green vehicle investments virtually non-existent. In this study we develop a two-stage game theoretic model that helps evaluate, from both policy and organizational perspectives, the implications of greening of transportation fleets. Various parameters are evaluated including factors such as innovations in green vehicle technology, levels of service differences, cost of fuel, adjusting tax policy, regulatory compliance requirements, and adaptation costs. This evaluation provides practical insights into actions that could be considered by regulators and organizations to encourage environmental investments.

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