New entropy weight-based TOPSIS for evaluation of multi-objective job-shop scheduling solutions

Facing with an obtained set of Pareto solutions on multi-objective job-shop scheduling problems, its core issue is how to evaluate the best-compromise solution from these non-dominated solutions for decision maker. TOPSIS as a multi-criteria decision making method is introduced into the evaluation of these Pareto solutions. The traditional Entropy weight approach used to calculate the weights of each criterion fails to faithfully transform the information from the Entropy value to Entropy weight, and an abrupt change of Entropy weight arises while facing with a very slight change of Entropy values when these Entropy values are close to 1. To address them, a new transformation formula from the Entropy value to Entropy weight is proposed to not only heritage the originally good performance but also make up the existing deficiency. Finally, the result of an illustrated example shows that the feasibility and accuracy of the proposed approach.