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Titlebook: Simulated Evolution and Learning; 11th International C Yuhui Shi,Kay Chen Tan,Yaochu Jin Conference proceedings 2017 Springer International

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0302-9743 and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. .The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary mach
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A Simple Brain Storm Optimization Algorithm via Visualizing Confidence Intervalsd study the brain storm optimization algorithm in depth. Through analyzing numerical effects of different components of brain storm optimization, a simplified brain storm optimization algorithm is developed. It is tested and shown to perform better than the original brain storm optimization algorith
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Simulated Annealing with a Time-Slot Heuristic for Ready-Mix Concrete Deliveryheduling constraints that have to be satisfied by considering the tradeoff between production and distribution costs. Various exact and heuristic methods have been developed to address the CDP. However, due to the limitation of the exact methods for dealing with such a complex problem, (meta-)heuris
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A Sequential Learnable Evolutionary Algorithm with a Novel Knowledge Base Generation Methodproblems. An algorithm pool consists of set of established algorithms. A knowledge base is trained offline. SLEA uses the algorithm-problem features to select the best algorithm from the algorithm pool. Given a problem, the default algorithm is run for the initial round. After that, an algorithm-pro
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Using Parallel Strategies to Speed up Pareto Local SearchPLS requires a long time to find high-quality solutions. In this paper, we propose and investigate several parallel strategies to speed up PLS. These strategies are based on a parallel multi-search framework. In our experiments, we investigate the performances of different parallel variants of PLS o
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Differential Evolution Based Hyper-heuristic for the Flexible Job-Shop Scheduling Problem with Fuzzyy processing time (FJSPF). In the DEHH scheme, five simple and effective heuristic rules are designed to construct a set of low-level heuristics, and differential evolution is employed as the high-level strategy to manipulate the low-level heuristics to operate on the solution domain. Additionally,
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ACO-iRBA: A Hybrid Approach to TSPN with Overlapping Neighborhoodsons Problem). In this paper, we propose a hybrid TSPN solution named ACO-iRBA in which the TSP and TPP tasks are tackled simultaneously by ACO (Ant Colony Optimization) and iRBA, an improved version of RBA (Rubber Band Algorithm), respectively. A major feature of ACO-iRBA is that it can properly han
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