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Multiple Objective Decision Making — Methods and Applications
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“Pareto optimization has emerged as the preferred method for MPO, as it allows for the identification of trade-offs between objectives, leading to the discovery of non-dominant solutions (101).”
From Artificial Intelligence for Drug Discovery: Are We There Yet? (2024) · cites this paper as [101]
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Ferreira, J. C., Fonseca, C. M., Denysiuk, R., et al. (2017) · Journal of Multi-Criteria Decision Analysis · doi:10.1002/mcda.1610 · Cited by 10
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Using efficient feasible directions in interactive multiple objective linear programming
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Goal Programming: Potential and Limitations for Agricultural Economics
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A multiobjective programming framework for integrating timber and wildlife management
Mendoza, G. (1988) · Environmental Management · doi:10.1007/bf01873385 · Cited by 10
Multicriteria Decision Models with Specified Goal Levels
Dinkelbach, W. (1980) · Lecture notes in economics and mathematical systems · doi:10.1007/978-3-642-48782-8_5 · Cited by 10
Multi-objective optimization for AGV energy efficient scheduling problem with customer satisfaction
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Interactive Fuzzy Goal Programming approach in multi-response stratified sample surveys
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Downing, C. E., & Ringuest, J. L. (2002) · Decision Support Systems · doi:10.1016/s0167-9236(02)00011-8 · Cited by 9
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A PREEMPTIVE VALUE‐FUNCTION METHOD APPROACH FOR MULTIOBJECTIVE LINEAR PROGRAMMING PROBLEMS
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A sampling-based method for generating nondominated solutions in stochastic MOMP problems
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“multiobjective optimization problem by ®rst eliciting a decision maker's multiattribute utility function and then optimizing this function using an appropriate mathematical programming algorithm (Farquhar, 1984; Hwang and Masud, 1979; Keeney and Raia, 1976; Steuer, 1986).”
MethodOptimierung bei mehrfacher Zielsetzung
Isermann, H. (1991) · Springer eBooks · doi:10.1007/978-3-642-76844-6_5 · Cited by 9
Introduction to pareto optimal mine planning
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Optimization of Structural Systems under Reserve and Residual Reliability Requirements
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Multi-objective Optimization of a Multi-site Manufacturing Network
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“Various solution concepts for MOPs have been introduced and different approaches for solving them have been provided [21,36].”
BackgroundMethodAn IoT-Aware VNF Placement Proof of Concept in a Hybrid Edge-Cloud Smart City Environment
Rafique, Y., Leivadeas, A., & Ibnkahla, M. A. (2022) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc51071.2022.9772004 · Cited by 8
Closed-Loop Supply Chain Network Design with Flexible Capacity under Uncertain Environment
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Multi-objective optimization based real-time control for PEV hybrid energy management systems
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“…Augmented Weighted Tchebycheff problem, if the objectives are linear, results in the linear optimization problem, by introducing a slack variable k (Hwang & Masud, 1979): min kþ q XM i¼1 zi xð Þ z i (1) subject to wi zi xð Þ z i k 0; where, x is the decision variables vector, ziðxÞ are the…”
BackgroundUsing Shapley Values and Genetic Algorithms to Solve Multiobjective Optimization Problems
Wu, H.-C. (2021) · Symmetry · doi:10.3390/sym13112021 · Cited by 8
Multi-Objective Genetic Algorithm for Cluster Analysis of Single-Cell Transcriptomes
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“One approach is to optimize one objective function, while constraining the other objective functions [66].”
BackgroundCity Planning with a Multiobjective Genetic Algorithm and a Pareto Set Scanner
Balling, R. J., Taber, J. T., Day, K., et al. (2000) · Springer eBooks · doi:10.1007/978-1-4471-0519-0_19 · Cited by 8
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Using Zionts–Wallenius method to improve estimate of value efficiency in DEA
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Despotis, D. K., & Siskos, J. (1992) · Theory and Decision · doi:10.1007/bf00134047 · Cited by 8
Relaxation of constraints in lexicographic multiobjective programming problems
Rastegar, N., & Khorram, E. (2014) · Optimization · doi:10.1080/02331934.2014.929785 · Cited by 8
“[12] One of the ways to solve a multiobjective optimization problem is the lexicographic approach.”
BackgroundA FUZZY Q-ANALYSIS TAGUCHI METHOD FOR PARAMETER DESIGN WITH MULTIPLE QUALITY CHARACTERISTICS
Chi, S.-C., & Teng, J. (2007) · Experimental Techniques · doi:10.1111/j.1747-1567.2007.00185.x · Cited by 8
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Fuzzy set-based multiobjective allocation of resources: Solution algorithms and applications
Carvalho, M. B., Ekel, P., Martins, C. A. P. D. S., et al. (2005) · Nonlinear Analysis · doi:10.1016/j.na.2005.02.053 · Cited by 8
“1) is associated with determining a set of Pareto solutions Ω [4].”
BackgroundA new neural network approach to economic emission load dispatch
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Evolutionary algorithms for the design of a multivariable control for an aircraft flight control
Aranda, J., Parrilla, M., Ruipérez, P., et al. (2000) · AIAA Guidance, Navigation, and Control Conference and Exhibit · doi:10.2514/6.2000-4556 · Cited by 8
A flexible design methodology to solve energy management problems
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A Novel Heterogeneous Swarm Reinforcement Learning Method for Sequential Decision Making Problems
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“Naturally, such established MOGA methods as Goldberg’s Pareto ranking [8] or the utility function method with weights representing the relative preferences for the objectives [9] lend themselves as immediate choices.”
MethodAn interactive multi-objective gradient search
Ringuest, J. L., & Gulledge, T. R. (1992) · Operations Research Letters · doi:10.1016/0167-6377(92)90022-u · Cited by 8
Automated Approach for Optimizing Dynamic Systems
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Computational Techniques for Multicriteria Stochastic Optimization and Control
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The Role of Thermodynamic and Informational Entropy in Improving Real Estate Valuation Methods
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“In MCDM, researchers utilize Multi-objective optimization (MOO) weights of importance to be assigned to functions for simultaneous optimization problems [92].”
MethodMOBRO: multi-objective battle royale optimizer
Alp, S., Dehkharghani, R., Akan, T., et al. (2023) · The Journal of Supercomputing · doi:10.1007/s11227-023-05676-4 · Cited by 7
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Constructing and evaluating a master surgery schedule using a service-level approach
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“A non-dominate solution is one in which improvement in one target is not possible without jeopardizing the other [20].”
BackgroundChen, X., Lin, H. W., & Murata, T. (2011) · IEEJ Transactions on Electrical and Electronic Engineering · doi:10.1002/tee.21695 · Cited by 7
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Applying multiobjective RBFNNs optimization and feature selection to a mineral reduction problem
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Metadata
- Authors
- Hwang, C.-L., & Masud, A. S. M.
- Affiliations
- New Mexico State University (US)
- Venue
- Lecture Notes in Economics and Mathematical Systems
- Publisher
- Springer Berlin Heidelberg
- Published
- 1979
- ISSN
- 0075-8442 (ISSN-L)
- OpenAlex
- W4233757421
- Cited by
- 1,186
- References
- 0
- Citations by year
- 2026: 16 · 2025: 31 · 2024: 30 · 2023: 41 · 2022: 33 · 2021: 50 · 2020: 32 · 2019: 45 · 2018: 42 · 2017: 52 · 2016: 51 · 2015: 61 · 2014: 45 · 2013: 35 · 2012: 35
- FWCI
- 11.74
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in economics and mathematical systems (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Multi-Criteria Decision Making
- Social Sciences › Decision Sciences › Management Science and Operations Research › Optimization and Mathematical Programming
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
- Keywords
- multi-objective decision making, computational methods, multi-objective optimization
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