مدل اقتباسی پیشرفته و یک الگوریتم از عوامل ارزیابی در رتبه بندی اتوماتیک تامین کننده

Intelligent evaluation agent has been the most recent attempt toward automated supplier bid selection based on customer preferences. It has been proven to have advantages for successful supply chain coordination. Based on a formerly implemented real-time supply chain coordination system using intelligent agents, this work further investigates the problem to devise an intelligent fuzzy algorithm to evaluate supplier bids without direct human intervention. The general decision model of agent technology adoption has been explained in detail to provide a roadmap for managers and engineers in their movement toward multi-agent working environments. Then, the hybrid evaluation mechanism has been discussed step-by-step. Afterward, the approach has been carefully implemented and verified via a real-world case study. In this regard, a collection of twelve assessment criteria classified in two categories of customer suggestions and design specifications have been considered. This work has key advantages over earlier ones, including: modeling agent technology adoption in supply networks, description of an autonomous assessment mechanism using intelligent agents, making the best out of three useful methodologies of F-AHP-QFD, considering features of customer order and his/her preferences throughout the decision making process, and coordination of supply processes using a bidding system based on pervasive and ubiquitous computing mechanisms.

Putting the concept of autonomous real-time coordination of supply chains into action has been the main subject matter of our recent research and publications [1], [2], [3], [4], [5], [6], [7], [8] and [9]. The major purpose of the project has been to employ the power of ubiquitous and pervasive computing based on intelligent agents (as useful tools of distributed artificial intelligence) in order to design and implement different modules required in a typical supply chain coordination system. The detailed description of an autonomous system for supply chain coordination is presented in Appendix A. One of the critical jobs in such a system is to evaluate and select suppliers properly. The procurement phase in the coordination process plays a strategic role and external suppliers exert an ever growing pressure on the success or failure of a business [10] and [11]. This article proposes the basics of a supplier evaluation agent that selects the best supplier bid using a hybrid algorithm. This algorithm has been explained comprehensively and has been verified in practice. On the other hand, agent technology adoption in such environments needs an accurate decision model which has been explained in detail. The rest of this section introduces distributed artificial intelligence and supplier evaluation agent, and summarizes the following sections.

This work was a forward pace in turning the desire to have a real-time supply chain coordination system into practice. Besides, this method has been planned and verified to be implemented by autonomous agents. The approach brings two categories of evaluation criteria together; one based on customer preferences (CSs) and the other based on production characteristics (DSs). These premium features makes the model of great value to product/service supply chain managers. It has the key advantages of autonomy, comprehensiveness, integrity, and accuracy all at once. Moreover, the model may be applied in two general ways: manually and automatically. The question regarding on whether to adopt agent technology has been discussed in detail and the corresponding decision model may be used in this regard. The outcomes of the work have been qualified and verified through a real-world case study. The comparison between fuzzy and crisp rankings of supplier bids illustrates the conformity of this method for real-time assessment in practice. The model is extensible and may be applied to other cases of evaluation and selection of the best decision alternative. Some of them to mention are: assessment of service providers in a specific sector, selection of the best hub(s) in facility layout and location problems, choosing the best alternative in virtual environments, etc. This research was extension of the previous works on real-time supply chain coordination by means of MASs [1], [2], [3], [4], [5], [6], [7], [8] and [9]. The main contribution of the paper is introduction of supplier evaluation agent and its knowledge base engine. The hybrid algorithm proposed is to be implemented in the form of an evaluation engine and has unique features, such as combinatory nature, independence on human factors, self-governance, intelligence, precision of final rankings, straightforward to monitor the method of operation.