Suchergebnisse - "Multiple Objective Programming"

Multi-Objective Integer Programming: An Improved Recursive Algorithm von Ozlen, Melih, Burton, Benjamin A., MacRae, Cameron A. G.

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An improved algorithm exploiting the characteristics of a distance-based preference function to converge to preferred solutions von Karakaya, G., Köksalan, M.

“… We address the problem of choosing the most preferred of a set of alternatives that are defined by multiple criteria. We assume that the decision maker’s …”
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Multi-objective optimization of two-echelon vehicle routing problem: Vaccines distribution as a case study von Al Theeb, Nader, Abu-Aleqa, Mohammed, Diabat, Ali

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New ϵ−constraint methods for multi-objective integer linear programming: A Pareto front representation approach von Mesquita-Cunha, Mariana, Figueira, José Rui, Barbosa-Póvoa, Ana Paula

“… •Three algorithms to generate Pareto front representations are developed.•The algorithms are based on the epsilon-constraint method.•Diverse multi-objective …”
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Fifty years of multi-objective optimization and decision-making: From mathematical programming to evolutionary computation von Ehrgott, Matthias, Köksalan, Murat, Kadziński, Miłosz, Deb, Kalyanmoy

“… We review major developments in multi-objective optimization over the past decades. Although mathematical foundations and basic concepts have been established …”
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A coevolutionary technique based on multi-swarm particle swarm optimization for dynamic multi-objective optimization von Liu, Ruochen, Li, Jianxia, fan, Jing, Mu, Caihong, Jiao, Licheng

“… •A coevolutionary multi-swarm particle swarm optimizer is proposed.•All swarms utilize an information sharing strategy to evolve cooperatively.•A velocity …”
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Multi-objective optimization of a two-echelon vehicle routing problem with vehicle synchronization and ‘grey zone’ customers arising in urban logistics von Anderluh, Alexandra, Nolz, Pamela C., Hemmelmayr, Vera C., Crainic, Teodor Gabriel

“… •The ’grey zone’ improves the solution above all for clustered instances.•City layouts with the city center in the middle of the city profit most.•The …”
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Multi-criteria optimization and decision-making in radiotherapy von Breedveld, Sebastiaan, Craft, David, van Haveren, Rens, Heijmen, Ben

“… •Layman’s background in radiotherapy treatment planning is given.•Describing the complexity of decision-making in medicine.•Review of used multi-criteria …”
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A novel multi-objective particle swarm optimization with multiple search strategies von Lin, Qiuzhen, Li, Jianqiang, Du, Zhihua, Chen, Jianyong, Ming, Zhong

“… •Two search strategies are designed for updating the velocity of each particle.•An evolutionary search strategy is performed on the external archive of PSO.•A …”
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Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods von Rodríguez-Espíndola, Oscar, Albores, Pavel, Brewster, Christopher

“… •A model was designed to optimise logistic decisions and minimise agencies involved.•Multi-objective optimisation and equity are incorporated in the …”
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Generator sets for the Minkowski sum problem von Lyngesen, Mark, Gadegaard, Sune Lauth, Nielsen, Lars Relund

“… This paper develops a new theoretical framework for generator sets in the context of Minkowski Sum Problems (MSPs) arising in multi-objective optimization. In …”
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Objectives and methods in multi-objective routing problems: a survey and classification scheme von Zajac, Sandra, Huber, Sandra

“… •Our survey offers a wide overview of which application-oriented multi-objective routing problems are treated at each planning level and what kind of trade-off …”
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A multi-objective stochastic programming approach for supply chain design considering risk von Azaron, A., Brown, K.N., Tarim, S.A., Modarres, M.

“… In this paper, we develop a multi-objective stochastic programming approach for supply chain design under uncertainty. Demands, supplies, processing, …”
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Topsis for multiple objective programming with rough decision set von Abou-El-Enien, Tarek, Abo-Elnaga, Y., Mohammad, Kamilia

“… Many optimization problems have competing objectives that require being optimized at the same time. These problems are called ?multiple objective programming …”
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TRANSFORM-ANN for online optimization of complex industrial processes: Casting process as case study von Miriyala, Srinivas Soumitri, Subramanian, Venkat R., Mitra, Kishalay

“… •Novel Neural Network building algorithm for application in operational research.•It enables optimal estimation of architecture, transfer function and training …”
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Finding preferred solutions under weighted Tchebycheff preference functions for multi-objective integer programs von Karakaya, G., Köksalan, M.

“… •Considers weighted Tchebycheff preference functions.•Develops an interactive algorithm that finds the most preferred solution.•Exploits the characteristics of …”
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Few-shot learning and deep predictive models for cost optimization and carbon emission reduction in energy-water management von Zhao, Wei, Chen, Hao, Yazan, Devrim Murat, Taghavifar, Hadi, Lyu, Yucheng, Bulis, Aldis

“… Effective management of energy and water resources is essential for mitigating environmental impacts and enhancing sustainability. This paper proposes a …”
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Warm-starting lower bound set computations for branch-and-bound algorithms for multi objective integer linear programs von Forget, Nicolas, Gadegaard, Sune Lauth, Nielsen, Lars Relund

“… •Develops a branch-and-bound algorithm for multi-objective integer problems.•Uses the linear relaxation as a lower bound set in the algorithm.•Warm-starts the …”
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Non-contour efficient fronts for identifying most preferred portfolios in sustainability investing von Steuer, Ralph E., Utz, Sebastian

“… •The paper provides a framework for solving the three-objective Markowitz problem where sustainability in the form of ESG is the third objective.•With no clear …”
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New Dynamic Programming algorithm for the Multiobjective Minimum Spanning Tree problem von Maristany de las Casas, Pedro, Sedeño-Noda, Antonio, Borndörfer, Ralf

“… The Multiobjective Minimum Spanning Tree (MO-MST) problem generalizes the Minimum Spanning Tree problem by weighting the edges of the input graph using vectors …”
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