Optimization of Agricultural Machinery Allocation in Heilongjiang Reclamation Area Based on Particle Swarm Optimization Algorithm

Aiming at the imbalance of seasonal agricultural machinery operations in different regions and the low efficiency of agricultural machinery, an experiment is proposed to use particle swarm algorithm to plan agricultural machinery paths to solve the current problems in agricultural machinery operations. Taking the harvesting of autumn soybeans at Jianshan Farm in Heilongjiang Reclamation Area as the experimental object, this paper constructs the optimization target model of the maximum net income of farm machinery households, and uses particle swarm algorithm to carry out agricultural machinery operation distribution and path planning gradually. In this paper, by introducing 0 - 1 mapping, the improved algorithm adopts continuous decision variables to solve the optimization of discrete variables in agricultural machinery operations. The test results show that the particle swarm algorithm can realize the optimal allocation of agricultural machinery path, and the particle swarm algorithm is scientific and explanatory to solve the agricultural machinery allocation problem. This research can provide a scientific basis for farm agricultural machinery allocation and decision analysis

Nash Equilibria, collusion in games and the coevolutionary particle swarm algorithm

In recent work, we presented a deterministic algorithm to investigate collusion between players in a game where the players’ payoff functions are subject to a variational inequality describing the equilibrium of a transportation system. In investigating the potential for collusion between players, the diagonalization algorithm returned a local optimum. In this paper, we apply a coevolutionary particle swarm optimization (PSO) algorithm developed in earlier research in an attempt to return the global maximum. A numerical experiment is used to verify the performance of the algorithm in overcoming local optimum

An Algorithm to Determine Peer-Reviewers

The peer-review process is the most widely accepted certification mechanism for officially accepting the written results of researchers within the scientific community. An essential component of peer-review is the identification of competent referees to review a submitted manuscript. This article presents an algorithm to automatically determine the most appropriate reviewers for a manuscript by way of a co-authorship network data structure and a relative-rank particle-swarm algorithm. This approach is novel in that it is not limited to a pre-selected set of referees, is computationally efficient, requires no human-intervention, and, in some instances, can automatically identify conflict of interest situations. A useful application of this algorithm would be to open commentary peer-review systems because it provides a weighting for each referee with respects to their expertise in the domain of a manuscript. The algorithm is validated using referee bid data from the 2005 Joint Conference on Digital Libraries.Comment: Rodriguez, M.A., Bollen, J., "An Algorithm to Determine Peer-Reviewers", Conference on Information and Knowledge Management, in press, ACM, LA-UR-06-2261, October 2008; ISBN:978-1-59593-991-

A Coevolutionary Particle Swarm Algorithm for Bi-Level Variational Inequalities: Applications to Competition in Highway Transportation Networks

A climate of increasing deregulation in traditional highway transportation, where the private sector has an expanded role in the provision of traditional transportation services, provides a background for practical policy issues to be investigated. One of the key issues of interest, and the focus of this chapter, would be the equilibrium decision variables offered by participants in this market. By assuming that the private sector participants play a Nash game, the above problem can be described as a Bi-Level Variational Inequality (BLVI). Our problem differs from the classical Cournot-Nash game because each and every player’s actions is constrained by another variational inequality describing the equilibrium route choice of users on the network. In this chapter, we discuss this BLVI and suggest a heuristic coevolutionary particle swarm algorithm for its resolution. Our proposed algorithm is subsequently tested on example problems drawn from the literature. The numerical experiments suggest that the proposed algorithm is a viable solution method for this problem

Adaptive chaotic particle swarm algorithm for isogeometric multi-objective size optimization of FG plates

An effective multi-objective optimization methodology that combines the isogeometric analysis (IGA) and adaptive chaotic particle swarm algorithm is presented for optimizing ceramic volume fraction (CVF) distribution of functionally graded plates (FGPs) under eigenfrequencies. The CVF distribution is represented by the B-spline basis function. Mechanical behaviors of FGPs are obtained with NURBS-based IGA and the recently developed simple first-order shear theory. The design variables are the CVFs at control points in the thickness direction, and the optimization objective is to minimize the mass of structure and maximize the first natural frequency. A recently developed multi-objective adaptive chaotic particle swarm algorithm with high efficiency is employed as an optimizer. All desirable features of the developed approach will be illustrated through four numerical examples, confirming its effectiveness and reliability

Robust Design by Antioptimization for Parameter Tolerant GaAs/AlOx High Contrast Grating Mirror for VCSEL Application

A GaAs/AlOx high contrast grating structure design which exhibits a 99.5% high reflectivity for a 425nm large bandwidth is reported. The high contrast grating (HCG) structure has been designed in order to enhance the properties of mid-infrared VCSEL devices by replacing the top Bragg mirror of the cavity. A robust optimization algorithm has been implemented to design the HCG structure not only as an efficient mirror but also as a robust structure against the imperfections of fabrication. The design method presented here can be easily adapted for other HCG applications at different wavelengths.Comment: (c) 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists or reuse of any copyrighted components of this work in other work

Population structure and particle swarm performance

The effects of various population topologies on the particle swarm algorithm were systematically investigated. Random graphs were generated to specifications, and their performance on several criteria was compared. What makes a good population structure? We discovered that previous assumptions may not have been correct.(undefined

A Hybrid Approach Based on PSO and Hadamard Difference Sets for the Synthesis of Square Thinned Arrays

A hybrid approach for the synthesis of planar thinned antenna arrays is presented. The proposed solution exploits and combines the most attractive features of a particle swarm algorithm and those of a combinatorial method based on the noncyclic difference sets of Hadamard type. Numerical experiments validate the proposed solution, showing improvements with respect to previous results. (c) 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works