A multiobjective approach for finding equivalent inverse images of Pareto-optimal objective vectors
Günter Rudolph, Mike Preuß
Abstract
Günter Rudolph, Mike Preuß
Abstract
Supply bottlenecks or sudden changes in legal regulations may lead to the situation that certain factor combinations for producing some commodity cannot be used any longer. In this case it is important to know alternative factor combinations leading to a product with identical characteristics represented by a Pareto-optimal objective vector of a multiobjective optimization problem. Here, we present a biobjective approach that finds equivalent inverse images of a given Pareto-optimal objective vector, provided they exist.
OpenAlex reports 12 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Supply bottlenecks or sudden changes in legal regulations may lead to the situation that certain factor combinations for producing some commodity cannot be used any longer. In this case it is important to know alternative factor combinations leading to a product with identical characteristics represented by a Pareto-optimal objective vector of a multiobjective optimization problem. Here, we present a biobjective approach that finds equivalent inverse images of a given Pareto-optimal objective vector, provided they exist.
Key concepts: Pareto principle, Multi-objective optimization, Pareto optimal, Mathematical optimization, Inverse, Pareto efficiency, Product (mathematics), Pareto analysis