Implementation of a Constrained Quantum Optimization Method in Resource Distribution Management with Considering Queueing Scenarios

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Sandor Imre ◽  
Sara El Gaily
Keyword(s):  
Resource Distribution ◽  
Optimization Method ◽  
Distribution Management ◽  
Quantum Optimization

scholarly journals Research and Application on a Novel Clustering Algorithm of Quantum Optimization in Server Load Balancing

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Dong Yumin ◽  
Xiao Shufen ◽  
Jia Fanghua ◽  
Li Jinhai
Keyword(s):  
Clustering Algorithm ◽  
Simulated Annealing Algorithm ◽  
Optimization Method ◽  
Optimization Scheme ◽  
Analog Simulation ◽  
Energy Field ◽  
Network Cluster ◽  
Simulation And Experiment ◽  
Annealing Algorithm ◽  
Quantum Optimization

A quantum optimization scheme in network cluster server task scheduling is proposed. We explore and research the distribution theory of energy field in quantum mechanics; specially, we apply it to data clustering. We compare the quantum optimization method with genetic algorithm (GA), ant colony optimization (ACO), simulated annealing algorithm (SAA). At the same time, we prove its validity and rationality by analog simulation and experiment.

scholarly journals Optimal Analysis of Human Resources Allocation in Colleges and Universities Based on Internet of Things Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ai Zhang ◽  
Zhengmao Ju ◽  
Yiling Liu
Keyword(s):  
Internet Of Things ◽  
Human Resources ◽  
Real Time ◽  
Human Resource ◽  
Resource Distribution ◽  
Optimization Method ◽  
Requirements Analysis ◽  
Manufacturing Resources ◽  
Real Time Information ◽  
Time Information

This article takes the development and superiority of the human resource system under the IoT technology as the background and adopts the popular IoT architecture and the current latest technical theories to develop and improve the human resource management system. First, we introduce the establishment of the J2EE development environment and then introduce the realization of the three layers of the overall IoT architecture of the system, namely, the realization of the presentation layer, the realization of the layer, and the realization of the data and then the realization of the main modules of the system; finally, we explain the function test of some modules of the system. After that, we mainly analyze the requirements of the system, first the overall requirements analysis and then the function and nonfunctional requirements analysis of the system. On the basis of perfecting the service-oriented modeling of manufacturing resources, the integration and optimization of resources are carried out according to the requirements of manufacturing tasks, and the discovery mechanism and matching methods of manufacturing resource services are studied to reduce the solution space of resource allocation. Aiming at the problem of optimal utilization of manufacturing resources, this paper establishes a scientific and reasonable evaluation index system to reduce resource service costs and improve resource utilization. At the same time, after analyzing the problem of real-time distribution of resources in the manufacturing Internet of Things environment, the real-time information of resource distribution is designed. The interactive mechanism and a two-tier optimization method based on real-time information-driven resource distribution tasks are proposed. The simulation experiment results show that the optimization method proposed in this paper, compared with the traditional resource distribution method, not only reduces the carrying distance of human resource distribution but also reduces the empty load rate, thereby reducing the waste of human resources.

Optimization Method of Superelevation Transition for Oval Racing Tracks

CICTP 2019 ◽  
2019 ◽  
Author(s):  
Yuchen Wang ◽  
Tao Lu ◽  
Hongxing Zhao ◽  
Zhiying Bao
Keyword(s):  
Optimization Method

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Dimensioning a recovery boiler furnace using mathematical optimization

TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN
Keyword(s):  
Radial Basis Function Network ◽  
High Capacity ◽  
Mathematical Optimization ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Performance Criteria ◽  
Boiler Furnace ◽  
Starting Point ◽  
Recovery Boiler ◽  
Base Design

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.

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