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The main idea of this research is to devise the smart module to pick the best supplier bid(s) automatically. The hybrid model is composed of three useful tools: fuzzy logic, AHP, and QFD. The approach has been carefully implemented and verified via a real-world case study in a medium-to-large industry manufacturing vehicle tires and other rubber products. A collection of 12 assessment criteria classified into two categories have been considered. Eight factors are derived from customer suggestions and the other four are design specifications required to manufacture the product. The main outcomes are: a hybrid autonomous model to evaluate supplier bids without direct human intervention; devising a hybrid three-module method and overcoming complexity of computations in resulting algorithm by means of agents; outlining the best criteria to assess suppliers; evaluating the suppliers based on voice of customer during all stages of the process; and discussing analysis, design, and implementation issues of the evaluation agent. The paper includes implications for development of an integrated total system for supply chain coordination. The most important advantages of this work over earlier researches on supplier selection are: implementation of an autonomous assessment mechanism using intelligent agents for the first time, making the best out of three widely applied methodologies all at once, evaluation process mainly based on features of customer order, coordination of supply job based on a bidding system, and portal-mediated operation and control.

The article proposes a hybrid model to be applied by evaluation agents to pick the best supplier bid(s) in real-time supply network coordination. Softbots act without direct human intervention and make use of three powerful techniques of fuzzy logic, quality function deployment and analytical hierarchical process to evaluate and select the best alternative(s). Suppliers are ranked based on both voice of customer and technical requirements via an online bidding system. The resulting evaluation engine is embedded in an integrated total system for supply chain coordination. The mechanism is verified in theory and practice and has been implemented in real-world cases.

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.