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A filtered beam search method for the m-machine permutation flowshop scheduling problem minimizing the earliness and tardiness penalties and the waiting time of the jobs
A filtered beam search method for the m-machine permutation flowshop scheduling problem minimizing the earliness and tardiness penalties and the waiting time of the jobs
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A filtered beam search method for the m-machine permutation flowshop scheduling problem minimizing the earliness and tardiness penalties and the waiting time of the jobs

Birgin, E.G. ; Ferreira, J.E. ; Ronconi, D.P.

Computers & operations research, 2020-02, Vol.114, p.104824, Article 104824 [Periódico revisado por pares]

New York: Elsevier Ltd

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2
A survey of models and algorithms for emergency response logistics in electric distribution systems. Part II: Contingency planning level
A survey of models and algorithms for emergency response logistics in electric distribution systems. Part II: Contingency planning level
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A survey of models and algorithms for emergency response logistics in electric distribution systems. Part II: Contingency planning level

Perrier, Nathalie ; Agard, Bruno ; Baptiste, Pierre ; Frayret, Jean-Marc ; Langevin, André ; Pellerin, Robert ; Riopel, Diane ; Trépanier, Martin

Computers & operations research, 2013-07, Vol.40 (7), p.1907-1922 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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3
A weighted-sum method for solving the bi-objective traveling thief problem
A weighted-sum method for solving the bi-objective traveling thief problem
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A weighted-sum method for solving the bi-objective traveling thief problem

Chagas, Jonatas B.C. ; Wagner, Markus

Computers & operations research, 2022-02, Vol.138, p.105560, Article 105560 [Periódico revisado por pares]

New York: Elsevier Ltd

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4
DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems: Hybrid Metaheuristics
DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems: Hybrid Metaheuristics
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DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems: Hybrid Metaheuristics

SANTANA-QUINTERO, Luis V ; HERNANDEZ-DIAZ, Alfredo G ; MOLINA, Julián ; COELLO COELLO, Carlos A ; CABALLERO, Rafael

Computers & operations research, 2010, Vol.37 (3), p.470-480 [Periódico revisado por pares]

Kidlington: Elsevier

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5
DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems
DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems
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DEMORS: A hybrid multi-objective optimization algorithm using differential evolution and rough set theory for constrained problems

Santana-Quintero, Luis V. ; Hernández-Díaz, Alfredo G. ; Molina, Julián ; Coello Coello, Carlos A. ; Caballero, Rafael

Computers & operations research, 2010-03, Vol.37 (3), p.470-480 [Periódico revisado por pares]

New York: Elsevier Ltd

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6
DILS: Constrained clustering through dual iterative local search
DILS: Constrained clustering through dual iterative local search
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DILS: Constrained clustering through dual iterative local search

González-Almagro, Germán ; Luengo, Julián ; Cano, José-Ramón ; García, Salvador

Computers & operations research, 2020-09, Vol.121, p.104979, Article 104979 [Periódico revisado por pares]

New York: Elsevier Ltd

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7
A filtered beam search method for the m-machine permutation flowshop scheduling problem minimizing the earliness and tardiness penalties and the waiting time of the jobs
A filtered beam search method for the m-machine permutation flowshop scheduling problem minimizing the earliness and tardiness penalties and the waiting time of the jobs
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Artigo 		Adicionar ao Meu Espaço

A filtered beam search method for the m-machine permutation flowshop scheduling problem minimizing the earliness and tardiness penalties and the waiting time of the jobs

Ernesto Julian Goldberg Birgin José Eurípedes Ferreira de Jesus Filho; Débora Pretti Ronconi 1968-

Computers & Operations Research Oxford v. 114, n. 1-14, p.104824, 2020

Oxford 2020

Localização: IME - Inst. Matemática e Estatística    (PROD-2970508 )(Acessar)

8
hCHAC: A family of MOACO algorithms for the resolution of the bi-criteria military unit pathfinding problem
hCHAC: A family of MOACO algorithms for the resolution of the bi-criteria military unit pathfinding problem
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hCHAC: A family of MOACO algorithms for the resolution of the bi-criteria military unit pathfinding problem

Mora, A.M. ; Merelo, J.J. ; Castillo, P.A. ; Arenas, M.G.

Computers & operations research, 2013-06, Vol.40 (6), p.1524-1551 [Periódico revisado por pares]

New York: Elsevier Ltd

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9
Integrating simulation and optimization to schedule loading operations in container terminals
Integrating simulation and optimization to schedule loading operations in container terminals
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Integrating simulation and optimization to schedule loading operations in container terminals

Zeng, Qingcheng ; Yang, Zhongzhen

Computers & operations research, 2009-06, Vol.36 (6), p.1935-1944 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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10
Investing in lead-time variability reduction in a collaborative vendor–buyer supply chain model with stochastic lead time
Investing in lead-time variability reduction in a collaborative vendor–buyer supply chain model with stochastic lead time
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Investing in lead-time variability reduction in a collaborative vendor–buyer supply chain model with stochastic lead time

Lin, Hsien-Jen

Computers & operations research, 2016-08, Vol.72, p.43-49 [Periódico revisado por pares]

New York: Elsevier Ltd

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Deste Autor:

  1. Birgin, E
  2. Sobral, F
  3. Gentil, J
  4. Ronconi, D
  5. Laborie, P

Neste Assunto:

  1. Computer Science
  2. Engineering
  3. Engineering, Industrial
  4. Science & Technology
  5. Technology

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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