An Approach to Securely Identifying Beneficial Collaboration in Decentralized Logistics Systems
Chris Clifton,
Ananth Iyer,
Richard Cho,
Wei Jiang,
Murat Kantarc
o
lu,
Jaideep Vaidya
Department of Computer Science, Purdue University, West Lafayette, Indiana 47907
Krannert School of Management, Purdue University, West Lafayette, Indiana 47907
Faculty of Business, University of New Brunswick Saint John, Saint John, New Brunswick Canada, E2L 4L5
Department of Computer Science, Purdue University, West Lafayette, Indiana 47907
Department of Computer Science, The University of Texas at Dallas, Richardson, Texas 75083
Management Science and Information Systems Department, Rutgers University, Newark, New Jersey 07102
clifton{at}cs.purdue.edu
aiyer{at}mgmt.purdue.edu
rcho{at}unbsj.ca
wjiang{at}cs.purdue.edu
muratk{at}utdallas.edu
jsvaidya{at}rbs.rutgers.edu
The problem of sharing manufacturing, inventory, or capacity to improve performance is applicable in many decentralized operational contexts. However, the solution of such problems commonly requires an intermediary or a broker to manage information security concerns of individual participants. Our goal is to examine use of cryptographic techniques to attain the same result without the use of a broker. To illustrate this approach, we focus on a problem faced by independent trucking companies that have separate pick-up and delivery tasks and wish to identify potential efficiency-enhancing task swaps while limiting the information they must reveal to identify these swaps. We present an algorithm that finds opportunities to swap loads without revealing any information except the loads swapped, along with proofs of the security of the protocol. We also show that it is incentive compatible for each company to correctly follow the protocol as well as provide their true data. We apply this algorithm to an empirical data set from a large transportation company and present results that suggest significant opportunities to improve efficiency through Pareto improving swaps. This paper thus uses cryptographic arguments in an operations management problem context to show how an algorithm can be proven incentive compatible as well as demonstrate the potential value of its use on an empirical data set.
Key Words: collaboration; routing; cryptography; space-filling curve; incentive compatible; algorithm
History: Received: January 9, 2004;
accepted: December 10, 2006.
Copyright © 2008 by INFORMS.
