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Titlebook: Recent Advances in Computational Optimization; Results of the Works Stefka Fidanova Book 2018 Springer International Publishing AG 2018 Com

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發(fā)表于 2025-3-26 23:15:04 | 只看該作者
Verification of Correctness of Parallel Algorithms in Practice, detail how to show that a parallel algorithm is correct. This process involves proving its safety and liveness. In our case study, we prove the correctness of our two parallel algorithms for the NP-hard pickup and delivery problem with time windows. Both algorithms (for minimizing the number of rou
32#
發(fā)表于 2025-3-27 02:16:55 | 只看該作者
Application of Fuzzy Cognitive Maps with Evolutionary Learning Algorithm to Model Decision Support historical data. FCM models learned from data are denser than those created by humans. We developed an evolutionary learning approach for fuzzy cognitive maps based on density and system performance indicators. It allows to select only the most significant connections between concepts and receive th
33#
發(fā)表于 2025-3-27 08:09:51 | 只看該作者
Meeting the Challenges of Optimized Memory Management in Embedded Vision Systems Using Operations Rign, simulation, and implementation more and more challenging. Memory management is among the main challenge that electronic designers have to face. In fact, it impacts heavily the main cost metrics, including area, performance (real-time aspect) and energy consumption, of modern-day electronic devi
34#
發(fā)表于 2025-3-27 12:20:01 | 只看該作者
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發(fā)表于 2025-3-27 17:22:05 | 只看該作者
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發(fā)表于 2025-3-27 19:09:36 | 只看該作者
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發(fā)表于 2025-3-28 01:55:34 | 只看該作者
38#
發(fā)表于 2025-3-28 03:57:32 | 只看該作者
1860-949X .Constitutes a comprehensive collection of extended contribu.This book presents new optimization approaches and methods and their application in real-world and industrial problems, and demonstrates how many of the problems arising in engineering, economics and other domains can be formulated as opti
39#
發(fā)表于 2025-3-28 07:43:38 | 只看該作者
40#
發(fā)表于 2025-3-28 11:32:17 | 只看該作者
On the Exact Solution of the Distance Geometry with Interval Distances in Dimension 1,nce of interval distances. Backtracking pruning is introduced in the algorithm for guaranteeing that all vertex positions in a given solution are actually feasible. The proposed algorithm is tested on a set of artificially generated instances in dimension?1.
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