Generation of efficient frontiers in multi-objective optimization problems by generalized data envelopment analysis.

DOI10.1016/S0377-2217(99)00469-5zbMath1125.90377OpenAlexW2047738453MaRDI QIDQ5928381

Hirotaka Nakayama, Y. B. Yun, Masao Arakawa, Tetsuzo Tanino

Publication date: 28 March 2001

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0377-2217(99)00469-5

zbMATH Keywords

Genetic algorithmsEfficient frontierGeneralized data envelopment analysisMulti-objective optimization

Mathematics Subject Classification ID

Multi-objective and goal programming (90C29) Management decision making, including multiple objectives (90B50) Approximation methods and heuristics in mathematical programming (90C59) Special problems of linear programming (transportation, multi-index, data envelopment analysis, etc.) (90C08)

Related Items

Multi-objective optimization based on meta-modeling by using support vector regression, Multiple criteria decision making with generalized DEA and an aspiration level method, Utilizing expected improvement and generalized data envelopment analysis in multi-objective genetic algorithms, Multicriteria allocation model of additional resources based on DEA: MOILP-DEA, Generation of Pareto optimal solutions using generalized DEA and PSO, Multi-objective optimization using statistical models, Evolving a multiobjective obstacle avoidance skill of a seven-link manipulator subject to constraints, A novel mixed Spider's web initial solution and data envelopment analysis for solving multi-objective optimization problems

Cites Work

• Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
• Measuring the efficiency of decision making units
• Theory of multiobjective optimization
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item