Preface: advances in theoretical and practical combinatorial optimization.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 1, doi. 10.1007/s10479-018-3072-z
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Works matching IS 02545330 AND DT 2019 AND VI 272 AND IP 1/2
Results: 21
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Optimal spare parts management for vessel maintenance scheduling.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 323, doi. 10.1007/s10479-018-2907-y
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3
Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 119, doi. 10.1007/s10479-018-2876-1
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4
Solving shift scheduling problem with days-off preference for power station workers using binary integer goal programming model.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 355, doi. 10.1007/s10479-018-2848-5
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5
Adaptive layout for operating theatre in hospitals: different mathematical models for optimal layouts.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 493, doi. 10.1007/s10479-018-2799-x
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6
Formulation and solution of a two-stage capacitated facility location problem with multilevel capacities.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 41, doi. 10.1007/s10479-017-2741-7
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7
A novel supplier selection method that integrates the intuitionistic fuzzy weighted averaging method and a soft set with imprecise data.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 139, doi. 10.1007/s10479-017-2718-6
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8
A note on linearized reformulations for a class of bilevel linear integer problems.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 99, doi. 10.1007/s10479-017-2694-x
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9
Maximizing the expected number of transplants in kidney exchange programs with branch-and-price.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 429, doi. 10.1007/s10479-017-2647-4
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10
Solving the capacitated clustering problem with variable neighborhood search.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 289, doi. 10.1007/s10479-017-2601-5
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11
Obstacle-aware optimization of offshore wind farm cable layouts.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 373, doi. 10.1007/s10479-017-2581-5
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12
A skewed general variable neighborhood search algorithm with fixed threshold for the heterogeneous fleet vehicle routing problem.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 243, doi. 10.1007/s10479-017-2576-2
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13
The incremental cooperative design of preventive healthcare networks.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 445, doi. 10.1007/s10479-017-2569-1
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14
Ascent-descent variable neighborhood decomposition search for community detection by modularity maximization.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 273, doi. 10.1007/s10479-017-2553-9
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15
Simulated annealing approach to nurse rostering benchmark and real-world instances.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 187, doi. 10.1007/s10479-017-2546-8
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16
An evolutionary approach to a combined mixed integer programming model of seaside operations as arise in container ports.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 69, doi. 10.1007/s10479-017-2539-7
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17
Managing facility disruption in hub-and-spoke networks: formulations and efficient solution methods.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 159, doi. 10.1007/s10479-017-2517-0
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18
Single-machine and parallel-machine serial-batching scheduling problems with position-based learning effect and linear setup time.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 217, doi. 10.1007/s10479-017-2481-8
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19
Product costing in the strategic formation of a supply chain.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 389, doi. 10.1007/s10479-017-2463-x
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20
A flow based pruning scheme for enumerative equitable coloring algorithms.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 3, doi. 10.1007/s10479-017-2451-1
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21
A polynomial time algorithm for the minimum flow problem in time-varying networks.
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- Annals of Operations Research, 2019, v. 272, n. 1/2, p. 29, doi. 10.1007/s10479-017-2450-2
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