Jiahai Wang

TL;DR: Six learning algorithms including biogeography-based optimization, particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, and population-based incremental learning are used to train a new dendritic neuron model (DNM) and are suggested to make DNM more powerful in solving classification, approximation, and prediction problems.

TL;DR: A novel JADE variant is presented by incorporating chaotic local search (CLS) mechanisms into JADE to alleviate this problem and has a superior performance in comparison with JADE and some other state-of-the-art optimization algorithms.

TL;DR: This paper investigates a practical variant of the vehicle routing problem (VRP), called VRP with simultaneous delivery and pickup and time windows (VRPSDPTW), in the logistics industry and shows that MOLS outperforms MOMA in most of instances.

TL;DR: A neuron model based on dendritic mechanisms and a phase space reconstruction (PSR) to analyze the Shanghai Stock Exchange Composite Index, Deutscher Aktienindex, N225, and DJI Average and shows that the attractors obtained can be observed intuitively in a three-dimensional search space, thereby allowing the characteristics of dynamic systems to be analyzed.

TL;DR: A two-stage multiobjective multidepot vehicle routing problem with time windows is proposed and a hybrid neighborhood structure is designed for solution improvement, which significantly outperforms two other representative algorithms.