Multiobjective programming and planning

By J. Cohon. 2004

1,276 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/c36c6abc268edaaeaec530b33d895e89cdc625b3

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Citations in the corpus

Topology Optimization of Heat and Mass Transfer Problems: Laminar Flow (2013, positive): “The set of solutions that requires a trade-off to be improved is well known as the Pareto front [27] and can be reached by using an aggregated objective function (AOF), also known as the weighted-sum approach, which is based on a linear combination of both objective functions.”
Stochastic Multiobjective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security (2009, methodology): “The most common approach is to calculate these ranges from the payoff table [35] as described”
An optimization framework for the development of efficient one-way car-sharing systems (2015, methodology): “Using the parameters presented in Table 1, we solved the model and generated the efficient frontier provided in Figure 9 by using weighted sum method [29].”
The orienteering problem with stochastic profits (2008, methodology): “To generate the extreme points of H, we use the weighted sum method, which is a well-known bi-objective optimization method (Cohon, 1978).”
Stochastic p-robust location problems (2006, methodology): “tradeofi, we used the constraint method of multi-objective programming ( Cohon 1978 )”
A review of multi-objective optimization: Methods and its applications (2018, neutral): “In the weighted-sum method (Cohon, 1983; Das & Dennis, 1997; Kim & de Weck, 2005; Messac, Sukam, & Melachrinoudis, 2000a; Messac, Sundararaj, Tappeta, & Renaud, 2000b; Odu & Charles-Owaba, 2013; Triantaphyllou, Shu, Sanchez, & Ray, 1998), all problems are combined into one problem using a weighted…”
Designing supply chains with sustainability considerations (2011, background): “Multiobjective optimisation (MOO), a well-established area within the field of operational research (Cohon 1978), is particularly suited for this type of problems.”
Integrated supply chain design models: a survey and future research directions (2007, methodology): “Shen and Daskin [75] propose two solution approaches, one based on the weighting method [16] and the other based on genetic algorithms, to solve this multiobjective model.”
Carbon market sensitive sustainable supply chain network design (2010, background): “Increasing regulatory legislations for carbon and waste management and the joint focus on corporate social responsibility and good citizenship mean that corporations must now pursue a Multi-Objective Optimization (MOO) to strike the best balance between these conflicting objectives (Cohon, 1978 [1])”
Effective implementation of the epsilon-constraint method in Multi-Objective Mathematical Programming problems (2009, methodology): “In the e-constraint method we optimize one of the objective functions using the other objective functions as constraints, incorporating them in the constraint part of the model as shown below [5,6] max f 1ðxÞ st f 2ðxÞP e2; f 3ðxÞP e3; .”
Topology Optimization Using the SIMP Method for Multiobjective Conductive Problems (2012, background): “The set of solutions that requires a trade-off to be improved is wellknown as the Pareto front, which has been defined by Cohon [25] as:”
Analysing trade-offs in resource and labour allocation by smallholder farmers using inverse modelling techniques: A case-study from Kakamega district, western Kenya (2007, methodology): “For linear models, multi-objective linear programming (MOP) methods can be used to analytically derive the set of efficient or non-dominated Pareto solutions (Cohon, 1978).”
Optimization of multiple satisfaction levels in portfolio decision analysis (2017, neutral): “These include the branch and bound algorithms [42] or the constraint method [13, 55].”