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Titlebook: Bioinspired Heuristics for Optimization; El-Ghazali Talbi,Amir Nakib Book 2019 Springer Nature Switzerland AG 2019 Bioinspired Heuristics.

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11#
發(fā)表于 2025-3-23 10:24:12 | 只看該作者
D. Leibovici,A. Sella,I. Y. Siegel,A. Zismanthm (PSO) in Kuo and Han (Applied Mathematical Modelling 35:3905–3917, 2011, [.]) using four problems in the literature and an example of supply chain model. These results show that the proposed approach provides the optimal solution and outperforms HGAPSO for most test problems adopted from the literature.
12#
發(fā)表于 2025-3-23 17:37:21 | 只看該作者
Epidemiology of Renal Cell Carcinomaal Netwok (CHN) and Conflicts Minimization Heuristics to solve a quadratic reformulation of the CSP-MSP model in other words the Min-Conflict heuristic will improve the given CHN solution. So, the performance of the network is compared with the existing scheduling algorithms under various experimental conditions.
13#
發(fā)表于 2025-3-23 18:20:04 | 只看該作者
The Metabolic Basis of Kidney Cancerall instances. In this paper, we apply three local search-based metaheuristics for solving the problem. Results on 280 randomly generated instances with different sizes show the clear outperformance of the metaheuristic approaches over the exact method based on Mixed Integer Linear Programming.
14#
發(fā)表于 2025-3-23 22:25:25 | 只看該作者
15#
發(fā)表于 2025-3-24 05:56:25 | 只看該作者
Possibilistic Framework for Multi-objective Optimization Under Uncertainty, mono-objective and multi-objective cases. Secondly, we suggest an extension of two well-known Pareto-base evolutionary algorithms namely, SPEA2 and NSGAII. Finally, the extended algorithms are applied to solve a multi-objective Vehicle Routing Problem (VRP) with uncertain demands.
16#
發(fā)表于 2025-3-24 06:43:07 | 只看該作者
Storage Yard Management: Modelling and Solving,igated, and solutions are obtained through the use of heuristics and a commercial optimization package. The computational experiments (based in real cases) showed that the method is more efficient in producing a feasible solution than the solver.
17#
發(fā)表于 2025-3-24 14:36:38 | 只看該作者
Application of Genetic Algorithm for Solving Bilevel Linear Programming Problems,thm (PSO) in Kuo and Han (Applied Mathematical Modelling 35:3905–3917, 2011, [.]) using four problems in the literature and an example of supply chain model. These results show that the proposed approach provides the optimal solution and outperforms HGAPSO for most test problems adopted from the literature.
18#
發(fā)表于 2025-3-24 17:33:04 | 只看該作者
19#
發(fā)表于 2025-3-24 21:04:43 | 只看該作者
20#
發(fā)表于 2025-3-24 23:18:08 | 只看該作者
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