ACO trained ANN-based bid/no-bid decision-making. (1st January 2012)

• Record Type: Journal Article
• Authors: Shi, Huawang
• Is Part Of: International journal of modelling, identification and control. Volume 15:Number 4(2012)
• Page Start: 290
• Page End: 296
• Publication Date: 2012-01-01
• Subjects: ant colony optimisation -- ACO -- artificial neural network -- ANN -- bid/no-bid decision; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

Abstract

One of the most important decisions that has to be made by contractor firms is whether to bid or not to bid for a project, when an invitation has been received. For any construction company, being able to deal successfully with various bidding situations is of crucial importance, especially in today's highly competitive construction market. This paper presents an application of ant colony optimisation (ACO) algorithm and artificial neural network (ANN) to bid/no-bid decision making. The ACO algorithm is a novel heuristic bionic algorithm, which is based on the behaviour of real ants in nature searching for food. Neural network is used to express the non-linear function between the input and output of the bid/no-bid decision making of project. ACO algorithm is used to learn ANN. The new algorithm has the merits of both ACO algorithm and neural network. The proposed decision support system framework is of good value to contracting organisations in different construction markets.