Title page for ETD etd-06032004-230342


Type of Document Master's Thesis
Author Uma Gnanasekaran, Viswanath
Author's Email Address vumagn1@lsu.edu
URN etd-06032004-230342
Title Improved Opportunity Cost Algorithm for Carrier Selection in Combinatorial Auctions
Degree Master of Science (M.S.)
Department Industrial & Manufacturing Systems Engineering
Advisory Committee
Advisor Name Title
Gerald Knapp Committee Chair
Bhaba Sarker Committee Member
Thomas Ray Committee Member
Keywords
  • opportunity cost algorithm
  • combinatorial auctions
Date of Defense 2004-05-12
Availability unrestricted
Abstract
Transportation costs constitute up to thirty percent of the total costs involved in a supply chain. Outsourcing the transportation service requirements to third party logistics providers have been widely adopted, as they are economically more rational than owning and operating a service. Transportation service procurement has been traditionally done through an auctioning process where the auctioneer (shipper) auctions lanes (distinct delivery routes) to bidders (carriers). Individual lanes were being auctioned separately disallowing the carriers to express complements and substitutes. Using combinatorial auctions mechanism to auction all available lanes together would allow the carriers to take advantage of the lane bundles, their existing service schedule, probability of securing other lanes and available capacity to offer services at lower rates and be more competitive. The winners of the auction are the set of non-overlapping bids that minimize the cost for the shippers. The winner determination problem to be solved in determining the optimal allocation of the services in such kind of combinatorial auctions is a NP-hard problem. Many heuristics like approximate linear programming, stochastic local search have proposed to find an approximate solution to the problem in a reasonable amount of time. Akcoglu et al [22] developed the opportunity cost algorithm using the “local ratio technique” to compute a greedy solution to the problem. A recalculation modification to the opportunity cost algorithm has been formulated where opportunity costs are recalculated every time for the set of remaining bids after eliminating the bid chosen to be a part of the winning solution and its conflicts have eliminated. Another method that formulates the winning solution based on the maximum total revenue values calculated for each bid using the opportunity cost algorithm has also been researched.
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