A Multiregional Agricultural Machinery Scheduling Method Based on Hybrid Particle Swarm Optimization Algorithm
نویسندگان
چکیده
The reasonable scheduling of agricultural machinery can avoid their purposeless flow during the operational service and reduce cost centers. In this research, a multiregional model with time window was established considering timeliness operation. This divided into two stages: first stage, regions were through Voronoi diagram, farmlands distributed to intraregional second solved using hybrid particle swarm optimization (HPSO). algorithm improves performance by introducing crossover, mutation, elimination mechanism, linear differential inertia weight trigonometric function learning factor. Next, accuracy effectiveness are verified different experimental samples. results show that effectively cost, has advantages strong global ability, high stability, fast convergence speed. Subsequent comparison proves HPSO better in situations, solve problem, provides scheme for multiarea multifarmland operations.
منابع مشابه
Diversified Particle Swarm Optimization for Hybrid Flowshop Scheduling
The aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society ...
متن کاملsolving flexible job-shop scheduling problem using hybrid algorithm based on gravitational search algorithm and particle swarm optimization
job shop scheduling problem has significant importance in many researchingfields such as production management and programming and also combinedoptimizing. job shop scheduling problem includes two sub-problems: machineassignment and sequence operation performing. in this paper combination ofparticle swarm optimization algorithm (pso) and gravitational search algorithm(gsa) have been presented f...
متن کاملTask Scheduling Algorithm Based on Hybrid Particle Swarm Optimization in Cloud Computing Environment
Cloud computing environment can offer dynamic and elastic virtual resources to the end users on demand basis. Task scheduling should satisfy the dynamic requirements of users and also need to utilize the virtual resources efficiently in cloud environment, so that task scheduling in cloud is an NP-Complete problem. In this paper, we present a Hybrid Particle Swarm Optimization (HPSO) based sched...
متن کاملRoad Network Matching Method Based on Particle Swarm Optimization Algorithm
Combined the global optimization ability of particle swarm algorithm and memory capacity of tabu algorithm, this paper proposed an automatic vector road network matching method based on the combination of particle swarm optimization and tabu strategy. Firstly, the similarity between node entities is evaluated by means of geometric and topological characteristics. Then, the basic principle of gl...
متن کامل7 Hybrid Genetic : Particle Swarm Optimization Algorithm
This chapter proposes a hybrid approach by combining a Euclidian distance (EU) based genetic algorithm (GA) and particle swarm optimization (PSO) method. The performance of the hybrid algorithm is illustrated using four test functions. Proportional integral derivative (PID) controllers have been widely used in industrial systems such as chemical process, biomedical process, and in the main stea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Agriculture
سال: 2023
ISSN: ['2077-0472']
DOI: https://doi.org/10.3390/agriculture13051042