Intelligent evaluation of supplier bids using a hybrid technique in distributed supply chains

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.