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🏛️國立陽明交通大學機構典藏

Author: search.filters.author.Dzeng, RJSubject: search.filters.subject.genetic algorithm

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    Item type:Item,
    Intelligent agents for supporting construction procurement negotiation
    (2004-07-01)
    Dzeng, RJ
    ;
    Lin, YC
    ;
    土木工程學系
    ;
    Department of Civil Engineering
    Negotiation is commonly required to reach a final contractual agreement in construction material procurement. However, even simple negotiations often result in suboptimal agreements, thus 'leaving money on the table.' An automated system that could evaluate bids, negotiate to finalize the bid, and value the individual characteristics of negotiating parties would be useful to both contractors and suppliers. This study examines common negotiable issues and options for construction material procurement, and presents an agent-based system, named C-Negotiators, that helps a contractor and suppliers to negotiate via the Internet. Genetic algorithm is used to find the most beneficial agreement for all parties. and web-based development is used to improve negotiation efficiency. Experiments also were conducted and demonstrated that C-Negotiators improved negotiation efficiency by saving negotiation time and cost, and improved negotiation effectiveness by suggesting a better agreement with higher joint payoff. Although the increase in payoff was smaller than expected, the improvement should increase for more complex negotiation problems involving more issues and options, or complicated preferences and for inexperienced negotiators. The application of the system is mainly limited by its symmetric optimization, while procurement negotiations in the construction industry are biased towards the contractor, and also by user comfort with their preferences and negotiations being monitored by the system. (C) 2003 Elsevier Ltd. All rights reserved.
  • Thumbnail Image
    Item type:Item,
    Intelligent agent for supporting construction procurement negotiation
    (2004)
    Dzeng, RJ
    ;
    土木工程學系
    ;
    Department of Civil Engineering
    Negotiation is commonly required in the procurement of construction materials for general contractors. However, people often reach suboptimal agreements, thereby "leaving money on the table". As E-commerce is becoming popular, an automated system that could evaluate bids, conduct negotiation to finalize the bid, and value the characteristics of negotiating parties would be useful to both contractor and suppliers. This paper presents an agent-based system that allows negotiating parties to define their preferences of negotiable issues and options, and suggests the most beneficial agreement using the genetic algorithm. Experiments were also conducted to evaluate the system's performance on effectiveness and efficiency.