Investigation of matchmaking and a genetic algorithm for multilateral and integrative E-negotiations
Simone A. Ludwig, Larry Raisanen, S.M.S. Reyhani · 2005
Abstract:- An electronic market platform usually requires buyers and sellers to exchange offers-to-buy and offers-to-sell. The goal of this exchange is to reach an agreement on the suitability of closing transactions between buyers and sellers. In this paper we use multilateral and integrative e-negotiations to investigate our approach which attempts to find the best buyer-seller pairs, for an equal number of buyers and seller, using either matchmaking or a well-tested genetic algorithm: NSGA-II. The goal is to match as many buyers and sellers as closely as possible on five objectives (i.e., quality, quantity, price, delivery and payment) that vary randomly between a given range for buyers and are fixed for sellers. Experiments are performed and results are discussed for both approaches. The main finding is that there is a trade-off between solution quality and execution time: The genetic algorithm is capable of finding higher quality solutions than matchmaking when a suitable population size is employed, but matchmaking’s execution time is significantly faster. This allows in turn to predict which technique to use depending on quality and speed in an e-negotiation scenario.