Supplier Selection by the Pair of AR-NF-IDEA Models

Supplier selection is the process by which suppliers are reviewed, evaluated, and chosen to become part of a company’s supply chain. To select the best suppliers in the presence of cardinal data, ordinal data, nondiscretionary factors, and weight restrictions, this paper proposes a new model considering all of these assumptions. A numerical example demonstrates the application of the proposed method.

A New Look at Selecting Third-Party Reverse Logistics Providers

The use of Data Envelopment Analysis (DEA) in many fields is based on total flexibility of the weights. However, the problem of allowing total flexibility of the weights is that the values of the weights obtained by solving the unrestricted DEA program are often in contradiction to prior views or additional available information. Also, many applications of DEA assume complete discretionary of decision making criteria. However, they do not assume the conditions that some factors are nondiscretionary. To select the most efficient third-party reverse logistics (3PL) provider in the conditions that both weight restrictions and nondiscretionary factors are present, a methodology is introduced. A numerical example demonstrates the application of the proposed method.

Supplier Selection by the Pair of AR-NF-IDEA Models

Supplier selection is the process by which suppliers are reviewed, evaluated, and chosen to become part of a company’s supply chain. To select the best suppliers in the presence of cardinal data, ordinal data, nondiscretionary factors, and weight restrictions, this paper proposes a new model considering all of these assumptions. A numerical example demonstrates the application of the proposed method.

A New Look at Selecting Third-Party Reverse Logistics Providers

The use of Data Envelopment Analysis (DEA) in many fields is based on total flexibility of the weights. However, the problem of allowing total flexibility of the weights is that the values of the weights obtained by solving the unrestricted DEA program are often in contradiction to prior views or additional available information. Also, many applications of DEA assume complete discretionary of decision making criteria. However, they do not assume the conditions that some factors are nondiscretionary. To select the most efficient third-party reverse logistics (3PL) provider in the conditions that both weight restrictions and nondiscretionary factors are present, a methodology is introduced. A numerical example demonstrates the application of the proposed method.