ENPS-IPROMETHEE: Enzymatic Numerical P System-based Improved Preference Ranking Organization Method for Enrichment Evaluation

Abstract

Membrane Computing is a natural computing paradigm inspired by the structure and activity of a biological cell. Membrane-based models can be realized using P System and these models have multiple applications. Here, it is applied to solve a Multi-criteria Decision-Making (MCDM) problem. MCDM is one of the important area in Decision-Making. It involves ranking items from a given set of items based on multiple criteria and it has several applications in different broad arenas which include Economics, Engineering and Management. MCDM includes several clusters of techniques that have been divided based on its modes of operation. All the techniques available till now consider sequential computing paradigm as the base for computation but in this work a parallel technique is used. Here, Enzymatic Numerical P System (ENPS)-based MCDM technique is designed. ENPS is a variant of P System used specifically for numerical problems. The proposed model, ENPS-IPROMETHEE is based on Improved Preference Ranking Organization Method for Enrichment Evaluation (IPROMETHEE), a popular outranking-based MCDM method. The designed model is verified and tested using PeP and GPUPeP simulators which are used for simulating ENPS models. A membrane file generator tool called as P-Generator is developed for automatic membrane generation. Two standard, existing datasets are considered and the model is studied for its sensitivity. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.