Engineering Commons^™

Collaborative Optimization Of Production And Energy Consumption In Flexible Workshop, Ding Yu, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: Considering the problem of the multi-objective constrained flexible job-shop,the NSGA-Ⅱalgorithm based on hybrid mutation operator is proposed.In view of NSGA-II algorithm being prone to premature convergence,poisson average and gaussian operators are introduced to improve the global and local optimization ability of the algorithm.The optimal scheme is selected from the set of pareto solutions by adopting the strategy of FAHP-IEVM,which is the combination of subjective and objective evaluation method. The modified algorithm is tested and compared by a series of ZDT test functions.The results show that the convergence and diversity of the revised algorithm are improved obviously.The effectiveness of …

Geometry Optimization Of Building-Integrated Photovoltaic Sunshade, Seyedsoroush Sadatifar

Electronic Thesis and Dissertation Repository

Building-integrated photovoltaic (BIPV) systems are one of the growing applications of PV technology. These approaches allow PV panels to perform additional functions for the building, such as regulating interior lighting and incoming heat. In this work, we explore a design framework for optimizing the configuration of BIPV shading devices to optimize a combination of power generation, daylighting conditions within the building, and heating and cooling loads.

We develop a generalizable computational model and apply it to a case study for the Cornerstone Architecture Building in London, Ontario. We optimize the configuration of static and dynamic BIPV shading devices in both …

Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He

Journal of System Simulation

Abstract: There is a model-based algorithm for the optimization of multiple objective functions by means of black-box evaluation is proposed. The algorithm iteratively generates candidate solutions from a mixture distribution over the solution space and updates the mixture distribution based on the sampled solutions’ domination count, such that the future search is biased towards the set of Pareto optimal solutions. The proposed algorithm seeks to find a mixture distribution on the solution space so that each component of the mixture distribution is a degenerate distribution centered at a Pareto optimal solution and each estimated Pareto optimal solution is uniformly spread …

Design Optimization Of Coreless Axial-Flux Pm Machines With Litz Wire And Pcb Stator Windings, Murat G. Kesgin, Peng Han, Narges Taran, Damien Lawhorn, Donovin Lewis, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Coreless axial-flux permanent-magnet (AFPM) machines may be attractive options for high-speed and high-power-density applications due to the elimination of core losses. In order to make full use of the advantages offered by these machines and avoid excessive eddy current losses in windings, advanced technologies for winding conductors need to be employed to suppress the eddy effect, such as the Litz wire and printed circuit board (PCB). In this paper, the best practices for designing Litz wire/PCB windings are discussed and a brief survey of state of the art PCB winding technology is provided. Three coreless AFPM machines are mainly considered. …

Dynamic Environmental And Economic Dispatching Of Wind Farm Based On Multi-Objective, Le Wei, Xijin Li

Journal of System Simulation

Abstract: Wind farms are developing rapidly under the new policy on energy resources vigorously advocated by the state. Its output scheduling is very complex, and needs the integration of economic and environmental factors. Aiming at the large prediction error of wind power, in the dynamic environmental economic dispatch of wind farm, the cost of rotating reserve is taken into account within the generation cost, and the demand of wind power prediction error for rotating reserve capacity is taken into account within the constraint condition. Aiming at the minimum total cost of power generation, the minimum total pollutant emission and minimum …

Energy And Performance-Optimized Scheduling Of Tasks In Distributed Cloud And Edge Computing Systems, Haitao Yuan

Dissertations

Infrastructure resources in distributed cloud data centers (CDCs) are shared by heterogeneous applications in a high-performance and cost-effective way. Edge computing has emerged as a new paradigm to provide access to computing capacities in end devices. Yet it suffers from such problems as load imbalance, long scheduling time, and limited power of its edge nodes. Therefore, intelligent task scheduling in CDCs and edge nodes is critically important to construct energy-efficient cloud and edge computing systems. Current approaches cannot smartly minimize the total cost of CDCs, maximize their profit and improve quality of service (QoS) of tasks because of aperiodic arrival …

A Multi-Objective Model For Sustainable Perishable Food Distribution Considering The Impact Of Temperature On Vehicle Emissions And Product Shelf Life, Amin Gharehyakheh, Caroline C. Krejci, Jaime Cantu, K. Jamie Rogers

Industrial, Manufacturing, and Systems Engineering Faculty Publications

The food distribution process is responsible for significant quality loss in perishable products. However, preserving quality is costly and consumes a tremendous amount of energy. To tackle the challenge of minimizing transportation costs and CO2 emissions while also maximizing product freshness, a novel multi-objective model is proposed. The model integrates a vehicle routing problem with temperature, shelf life, and energy consumption prediction models, thereby enhancing its accuracy. Non-dominated sorting genetic algorithm II is adapted to solve the proposed model for the set of Solomon test data. The conflicting nature of these objectives and the sensitivity of the model to shelf …

Multi-Objective Topology Mapping Method For Network Emulation, Xiaofeng Wang, Chen Yang, Guangjie Zhang, Jianyu Chen

Journal of System Simulation

Abstract: Network emulation is an important support for the verification of new network technology, and effective mapping is the key to the emulation network topology. Considering the multiple resource requirements, a multi-objective topology mapping method (MOTM) for network emulation topology is proposed to realize the effective physical resources utilization. The method analyzes the resource requirements of nodes and links, assigns corresponding weights, converts the mapping problem into the graph partitioning problem, divides the graph by multi-level graph partitioning method, and forms a mapping strategy through remote throughput threshold optimization adjustment. The automatic deployment is implemented based on the …

Photovoltaic Systems On Dairy Farms: Financial And Renewable Multi-Objective Optimization (Farmoo) Analysis, Michael Breen, J. Upton, Michael D. Murphy

Publications

No abstract provided.

3d Printing Orientation Optimization Based On Non-Dominated Sorting Genetic Algorithm, Dai Ning, Lisong Ou, Renkai Huang, Liu Hao

Journal of System Simulation

Abstract: Part orientation is one of the key technologies in 3D Printing,which has important influence on the surface precision, machining time and machining cost of the part. This problem is a research hot point of how to balance the surface precision and machining time. The improved Non-dominated Sorting Genetic algorithm was proposed to solve the problem of part orientation optimization. The mathematical model of part surface accuracy and machining time were constructed. The chromosome model of part orientation and the adaptive crowding distance were established. The genetic operators of select, crossover and mutation were used to get a set of …

Boiler Combustion Optimization Based On Bayesian Neural Network And Genetic Algorithm, Haiquan Fang, Huifeng Xue, Li Ning, Fei Xi

Journal of System Simulation

Abstract: Neural network and genetic algorithm have been extensively used in boiler combustion optimization problems. But the traditional Back Propagation neural network's generalization ability is poor. The Bayesian regularization can improve the neural network's generalization ability. A boiler combustion multi-objective optimization method combining Bayesian regularization BP neural network and genetic algorithm （Bayes NN-GA）was researched. A number of field test data from a boiler was used to simulate the Bayesian neural network model. The results show that the thermal efficiency and NOx emissions predicted by the Bayesian neural network model show good agreement with the measured, and the optimal results show …

Improved Cuckoo Search Algorithm Applied To Multi-Objective Optimization Of Crowd Evacuation, Chongjie Dong, Liu Yi, Peng Yong

Journal of System Simulation

Abstract: The crowd evacuation problem is a multi-objective optimization problem in large public places under the emergency, but because of the conflict between multiple objectives in multi-objective optimization problem, it is difficult to make the multiple targets achieve the optimal at the same time. The most popular solution is an evolution multi objective optimization algorithm for the characteristics of heuristic search of population and the partial order relation. Cuckoo search algorithm is a new search algorithm which was found in the behavior of cuckoo nest spawning lies, the basic cuckoo search algorithm is lack of vitality, and search is slow. …

Best Viewpoint Selection For 3d Visualization Using Particle Swarm Optimization, Panpan Jia, Yanyang Zeng, Yunxia Feng

Journal of System Simulation

Abstract: The viewpoint selection is to automatically select one or more approximate optimal viewpoints in the viewpoints of multiple views, at the same time, it is related to the evaluation of the quality of the viewpoint. 3D visualization best viewpoint selection method based on particle swarm optimization algorithm was proposed. The viewpoint quality was evaluated by using the image information entropy and the image edge entropy, and the viewpoint was selected by the multi-objective intelligent optimization method. The basic flow begins with the initial viewpoint set, finding the best viewpoint by means of coding, particle evaluation, and particle update, which …

Improved Shuffled Frog-Leaping Algorithm For Solving Flexible Job Shop Scheduling Problem, Xiaoxing Zhang, Wang Yan, Dahu Yan, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the characteristics of flexible job shop scheduling problem, a multi-objective scheduling model with maximum completion time and minimum energy consumption was proposed. An improved shuffled frog leaping algorithm was developed. By designing the local updating strategy based on crossover operation of maximum preserved crossover (MPX) and shifting operation of single parent gene algorithm (PGA), it avoided the illegal solution and trimming of the algorithm. Additionally, it accelerated optimization rate of the algorithm. And the optimal solution of the group was optimized by the simplified neighborhood optimization strategy to prevent the algorithm from falling into the local optimum. …

Mathematical Modeling Approaches In Sustainable Food Supply Chains, Amin Gharehyakheh

Industrial, Manufacturing, and Systems Engineering Dissertations

Access to high quality and safe food is vital for sustainable development in societies. Perishable foods lose a major portion of their quality after harvesting until the consumption point due to poor storage and distribution conditions. Thus, improvements in food supply chain operations are very critical in the sustainable development of society and the industry. The first part of this dissertation seeks to find a cost-effective and reliable tool to monitor the quality loss and implementation of the least shelf life first-out inventory management policy in food banks. Application of the Gompertz model and Arrhenius equation based on time-temperature data …

Multi-Objective Signal Timing Optimal Model For Rural-Urban Fringe Area Intersection, Xiaoyu Zhang, Chunfu Shao

Journal of System Simulation

Abstract: With the acceleration of the urbanization process in our country, the road traffic problems in the urban-rural fringe area are becoming serious. In order to improve the traffic efficiency, environmental benefits and traffic safety, a multi-objective optimal model for signal timing is established under the comprehensive consideration of several factors, such as the delay, capacity, number of stops and vehicle emissions. The genetic algorithm is used to solve the problem. A typical intersection is taken as the example for the analysis and the improved design schemes can be achieved and evaluated by the road traffic simulation. The …

Multi-Objective Optimal Reactive Power Planning Under Load Demand And Wind Power Generation Uncertainties Using Ε-Constraint Method, Amir Hossein Shojaei, Ali Asghar Ghadimi, Mohammad Reza Miveh, Fazel Mohammadi, Francisco Jurado

Electrical and Computer Engineering Publications

© 2020 by the authors. This paper presents an improved multi-objective probabilistic Reactive Power Planning (RPP) in power systems considering uncertainties of load demand and wind power generation. The proposed method is capable of simultaneously (1) reducing the reactive power investment cost, (2) minimizing the total active power losses, (3) improving the voltage stability, and (4) enhancing the loadability factor. The generators' voltage magnitude, the transformer's tap settings, and the output reactive power of VAR sources are taken into account as the control variables. To solve the probabilistic multi-objective RPP problem, the "-constraint method is used. To test the effectiveness …

Mission Architecture Analysis: Exploring Long-Period Comets From Multiple Staging Orbits, Gabriel Prescinotti Vivan

Masters Theses

Objects that have retained pieces of information about the early Solar System are key to our understanding of its formation and evolutionary history. However, the high delta-V required to reach these objects, such as long-period comets or interstellar objects, makes designing an intercept mission at the time of detection impractical. In this thesis, multiple heliocentric staging orbits are explored to serve as departure positions for future missions, prior to objects’ detections. By utilizing more than one staging orbit concurrently, the set of objects that are reachable is expanded, therefore increasing mission feasibility. Delta-V maps are generated and superimposed; two-impulse burn …

Moea/D Algorithm Based On The Hybrid Framework For Multi-Objective Evolutionary Algorithm, Hongjun Tian, Wang Lei, Qidi Wu

Journal of System Simulation

Abstract: Aimto the difficulties of designing the bonding mechanism of global optimization algorithm and local search strategy for hybrid multi-objective evolutionary algorithm, and of improving the performance of multi-objective evolutionary algorithms, based on the feedback control idea, a systematic and modular hybrid MOEA/D algorithm combining the global optimization and local search is proposed. In the algorithm, a diversity measure method based on crowded entropy is designed; a local search strategy based on simplified quadratic approximation and population diversity enhancement strategy for MOEA/D is proposed. The numerical experiments show that the proposed HMOEA/D can achieve a balance between diversity …