Using data envelopment analysis to solve unconstrained two-objective binary integer linear programming

Autor:	Fuh-Hwa Franklin Liu, Tyrone T. Lin
Rok vydání:	2007
Předmět:	Set (abstract data type) Binary integer linear programming Mathematical optimization Data envelopment analysis Portfolio Effective method Focus (optics) Mathematics
Zdroj:	Journal of Information and Optimization Sciences. 28:129-144
ISSN:	2169-0103 0252-2667
DOI:	10.1080/02522667.2007.10699733
Popis:	A subset of projects, from a set of feasible projects, is treated as a portfolio.The problem of selecting and evaluating all possible collective projects is modeled as unconstrained binary integer linear programming (BILP). Data envelopment analysis (DEA) is an effective method for classifying all portfolios into efficient and inefficient subgroups. In this paper, we focus on the single input and output case and use DEA as a tool to solve the two-objective BILP. The inherent relationships between output-input ratios of projects, and DEA portfolio efficiencies are presented in this paper. These findings enable the efficient and inefficient portfolios to be identified by ratio analysis. Moreover, if project with non-positive input and/or output is included in the decision set, our method is also valid through changing variables from the original model.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a5e96fab79698c9d776b23dd91a6b0e0 https://doi.org/10.1080/02522667.2007.10699733 Zobrazit plný text záznamu