The grey wolf optimization (GWO) algorithm is widely utilized in many global applications. In this paper, a dynamic opposite learning-assisted optimizer (DOLGWO) was proposed to improve the search ability. Herein, learning (DOL) strategy adopted, which has an asymmetric space and can adjust with random point enhance exploitation exploration capabilities. To validate performance of DOLGWO algori...

In recent years, microservices have been very widely used as a new application development technology in edge computing, IoT, and cloud computing. Application containerization is one of its core technologies, which allows multiple containers to be deployed within the same physical node. Then single node could provide different services user. How rationally deploy on cluster nodes main research ...

Economic load dispatch (ELD) provides significant benefits to the operation of power system. It appears be a complex nonconvex optimization problem subject several equal and unequal constraints. The greedy sine-cosine nonhierarchical gray wolf optimizer (G-SCNHGWO) is introduced in this study solve ELD problems efficiently robustly. sine cosine functions assist search agents grey (GWO) algorith...

Optimization is a buzzword, whenever researchers think of engineering problems. This paper presents new metaheuristic named dingo optimizer (DOX) which motivated by the behavior (Canis familiaris dingo). The overall concept to develop this method involving collaborative and social dingoes. developed algorithm based on hunting dingoes that includes exploration, encircling, exploitation. All abov...

Abstract In this paper, a BP neural network model with 5-9-6 structure is constructed according to various fault gases and different types of drilling fluid. On the basis model, genetic algorithm gray wolf are used optimize threshold weight network. By applying system Horizontal Well Changshen #5 on site Grey Wolf algorithm, lost circulation problem in horizontal section reservoir was effective...

This study will solve the classical vehicle routing problem, goal is to generate k trips with shortest distance for h customers predetermined locations and needs.. The proposed solution problem a hybrid sine cosine algorithm. algorithm hybridized grey wolf optimizer, which used in combination methods of tournament selection, opposition learning, mutation crossover method build optimal plan mean...

In this work, a new metaheuristic algorithm, namely the hybrid pelican Komodo algorithm (HPKA), has been proposed. This is developed by hybridizing two shortcoming algorithms: Pelican Optimization Algorithm (POA) and Mlipir (KMA). Through hybridization, proposed designed to adapt advantages of both POA KMA. Several improvisations regarding are as follows. First, replaces randomized target with ...

A correction to this paper has been published: https://doi.org/10.1007/s11277-021-08444-w