Semantic diversity in Genetic Programming has proved to be highly beneficial in evolutionary search. We have witnessed a surge in the number of scientific works in the area, starting first in discrete spaces and moving then to continuous spaces. The vast majority of these works, however, have focused their attention on single-objective genetic programming paradigms, with a few exceptions focusing on Evolutionary Multi-objective Optimization (EMO). The latter works have used well-known robust algorithms, including the Non-dominated Sorting Genetic Algorithm II and the Strength Pareto Evolutionary Algorithm, both heavily influenced by the notion of Pareto dominance. These inspiring works led us to make a step forward in EMO by considering Multi-objective Evolutionary Algorithms Based on Decomposition (MOEA/D). We show, for the first time, how we can promote semantic diversity in MOEA/D in Genetic Programming.
Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood
车辆路径问题是组合优化研究的热点问题之一，具有重要的实用价值和方法论意义。然而，尽管方法学取得了广泛的进展，但最近的许多研究都受到了简单有效的开源解决方案方法的限制。考虑到当前算法的复杂性，重新实现正在成为一项困难而耗时的工作，需要对细节进行广泛的关注才能真正成功。在此背景下，我们利用这篇短文的机会，介绍了一个简单的-开源-实现的混合遗传搜索（HGS）专门的能力限制车辆路径问题（CVRP）。这种最先进的算法使用与Vidal等人（2012）相同的一般方法，但也包括过去十年研究中的其他方法改进和经验教训。特别是，它包括一个称为SWAP* 的额外邻域，该邻域包括在不同路由之间交换两个客户，而无需插入到位。正如我们的研究所强调的，有效地探索SWAP* 移动对本地搜索的性能有很大的贡献。此外，正如在Uchoa et al.（2017）的经典实例上与其他最近方法的实验比较中所观察到的那样，HGS仍然是解决方案质量，收敛速度和概念简单性方面的领先元启发式算法。
Large Neighborhood and Hybrid Genetic Search for Inventory Routing Problems
Shenzhen Research Institute of Big Data（深圳大数据研究院）；Department of Economics and Management, University of Brescia（布雷西亚大学经济与管理学院）；Faculty of DS&AI, College of Technology, National Economics University（国家经济大学技术学院数据科学与人工智能学院）；CIRRELT & SCALE-AI Chair in Data-Driven Supply Chains, Department of Mathematical and Industrial Engineering, Polytechnique Montreal（蒙特利尔理工学院数学与工业工程系 CIRRELT 及 SCALE-AI 数据驱动供应链讲席）
CoInGP: Convolutional Inpainting with Genetic Programming
Faculty of Electrical Engineering and Computing, University of Zagreb（萨格勒布大学电气工程与计算学院）；Dipartimento di Matematica e Geoscienze, Università degli Studi di Trieste（的里雅斯特大学数学与地球科学系）；Cyber Security Research Group, Delft University of Technology（代尔夫特理工大学网络安全研究组）；NOVA Information Management School (NOVA IMS), Universidade Nova de Lisboa（新里斯本大学NOVA信息管理学院）
