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Articles 1 - 30 of 37
Full-Text Articles in Engineering
Planning Modeling And Optimization Algorithm For 5g Indoor Distribution System, Shaoda Zeng, Hailin Liu
Planning Modeling And Optimization Algorithm For 5g Indoor Distribution System, Shaoda Zeng, Hailin Liu
Journal of System Simulation
Abstract: Most of the new services in 5G mobile communication technologies, including smart homes, smart factories, and virtual reality, take place in indoor scenes. Therefore, how to quickly plan and build a 5G indoor distribution system with low construction cost and low power loss is of great significance for telecom operators. This paper establishes a mathematical planning model of a 5G indoor distribution system, which is closer to the actual scenario. The model aims to minimize the deployment cost and the maximum output signal power deviation between antennas, and the constraint is to meet the expected output signal power of …
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng
Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng
Journal of System Simulation
Abstract: Addressing the issues such as signal loss, distraction, and bad wash-out effect caused by improper parameter selection in classic wash-out algorithms, an improved multi-objective artificial bee colony algorithm is proposed to optimize the filter parameters of the classical wash-out algorithm to improve the effect. For the problems in the initialization and local optimization of traditional swarm algorithm, Circle mapping and Pareto local optimization algorithm are introduced. The human perception error model, acceleration difference model, and displacement model are established, and the model function is used as the objective function, the parameters of the classical wash-out algorithm is optimized by …
A Multi-Objective Stochastic Programming Model For Resilient And Sustainable Supply Chains Under Uncertainty, Mohammad H. Majdfaghihi
A Multi-Objective Stochastic Programming Model For Resilient And Sustainable Supply Chains Under Uncertainty, Mohammad H. Majdfaghihi
Dissertations
Supply chain resilience (SCRES) and sustainable supply chain management (SSCM) have garnered significant attention in the field of Supply Chain Management (SCM) science. This heightened interest is largely attributable to the increasing frequency and severity of uncertainty and disruptions in global supply chains. Resilience is a beneficial approach to managing uncertainties and preparing for and mitigating the adverse consequences of Supply Chain (SC) disruptions. Sustainability is a key concept in SCM, driven by governmental regulations and heightened stakeholder and customer concerns for environmental and societal well-being. Studies on SCRES have traditionally focused on preparing for and reacting to disruptions and …
Research On Period Emergency Supply Distribution Optimization Under Uncertainty, Li Zhang, Mingling He, Qiushuang Yin, Ning Li, Le'an Yu
Research On Period Emergency Supply Distribution Optimization Under Uncertainty, Li Zhang, Mingling He, Qiushuang Yin, Ning Li, Le'an Yu
Journal of System Simulation
Abstract: Aiming at the uncertainty and multi-periodicity of emergency supply distribution, a novel period vehicle routing problem(PVRP) multi-objective optimization model is built and a three-step optimization method is proposed. A triangular fuzzy number is used to eliminate the uncertainty. An AHP approach is used to transform the multi-objective function into the single objective function. An improved ACO algorithm is proposed to solve the single objective optimization problem. By classical data set, the time effectiveness of proposed method on emergency supply distribution problem is verified. The computational advantage in convergence speed is proved by the comparative analysis of the proposed …
Flexible Job-Shop Scheduling Problem Based On Improved Wolf Pack Algorithm, Chaoyang Zhang, Liping Xu, Jian Li, Yihao Zhao, Kui He
Flexible Job-Shop Scheduling Problem Based On Improved Wolf Pack Algorithm, Chaoyang Zhang, Liping Xu, Jian Li, Yihao Zhao, Kui He
Journal of System Simulation
Abstract: An improved wolf pack algorithm is proposed for solving multi-objective scheduling optimization for flexible job shop problems. A multi-objective flexible job shop scheduling model is developed with the maximum completion time of the workpiece and the energy consumption of the machine as the optimization goals. An improved wolf pack algorithm is proposed for solving the shortcomings that traditional wolf pack algorithm is easy to fall into the local optimization. Through improving the intelligent behavior of the wolf pack algorithm, individual codes are designed from the two levels of job's process and machine, and POX(precedence operation crossover) cross operation is …
Multi-Objective Optimization Algorithm Based On Multi-Index Elite Individual Game Mechanism, Xu Wang, Weidong Ji, Guohui Zhou, Jiahui Yang
Multi-Objective Optimization Algorithm Based On Multi-Index Elite Individual Game Mechanism, Xu Wang, Weidong Ji, Guohui Zhou, Jiahui Yang
Journal of System Simulation
Abstract: In order to improve the convergence of multi-objective optimization algorithm and the diversity of optimization solution set, and alleviate the flown down of population in target space, a multi-objective optimization algorithm based on multi-attribute elite individual game mechanism is proposed. This paper uses Pareto dominance relationship and multi-index to comprehensively screen elite individuals. The elite individual game mechanism with K-means clustering is integrated with cross and mutation strategy, which effectively improves the convergence and diversity of the algorithm. A detailed convergence analysis of the algorithm is performed to prove the convergence of the algorithm. Eight representative comparison algorithms are …
Large-Scale Multi-Objective Natural Computation Based On Dimensionality Reduction And Clustering, Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin
Large-Scale Multi-Objective Natural Computation Based On Dimensionality Reduction And Clustering, Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin
Journal of System Simulation
Abstract: In multi-objective optimization problems, as the number of decision variables increases, the optimization ability decreases significantly. To solve "dimension disaster", a large-scale multi-objective natural computation method based on dimensionality reduction and clustering is proposed. The decision variables are optimized by locally linear embedding(LLE) to obtain the representation of high-dimensional variables in the low-dimensional space, then the individuals are grouped through K-means to select the appropriate guide individuals for the population to strengthen the convergence and diversity. To verify the effectiveness, the method is applied to the multi-objective particle swarm optimization algorithm and the non-dominated sorting genetic algorithm. The convergence …
Accelerating Manufacturing Decisions Using Bayesian Optimization: An Optimization And Prediction Perspective, Taofeeq Olajire
Accelerating Manufacturing Decisions Using Bayesian Optimization: An Optimization And Prediction Perspective, Taofeeq Olajire
Graduate Theses, Dissertations, and Problem Reports
Manufacturing is a promising technique for producing complex and custom-made parts with a high degree of precision. It can also provide us with desired materials and products with specified properties. To achieve that, it is crucial to find out the optimum point of process parameters that have a significant impact on the properties and quality of the final product. Unfortunately, optimizing these parameters can be challenging due to the complex and nonlinear nature of the underlying process, which becomes more complicated when there are conflicting objectives, sometimes with multiple goals. Furthermore, experiments are usually costly, time-consuming, and require expensive materials, …
Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu
Energy-Efficient Scheduling Of Multi-Objective Flexible Job Shop Considering Interval Processing Time, Hongliang Zhang, Renman Ding, Gongjie Xu
Journal of System Simulation
Abstract: Based on the comprehensive consideration of economic indicators and environmental factors, the energy-efficient scheduling problem of multi-objective flexible job shop with uncertain processing time is studied. The interval number is used to describe uncertain processing time of the workpiece, and the optimization model for energy-efficient problem of interval flexible job shop scheduling is established to minimize the maximum interval completion time and total energy consumption. According to the domination relation of interval possibility degree, an effective interval multi-objective evolutionary algorithm is designed. The simulation experiments of the interval multi-objective evolutionary algorithm, SPEA-II and NSGA-II are carried out through 15 …
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Theses and Dissertations
Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …
Optimization Of Household Electricity Consumption Period Based On Improved Multi-Objective Particle Swarm Optimization, Xiuying Yan, Miaomiao Dang
Optimization Of Household Electricity Consumption Period Based On Improved Multi-Objective Particle Swarm Optimization, Xiuying Yan, Miaomiao Dang
Journal of System Simulation
Abstract: Aiming at the household power load scheduling optimization, three objectives of the cost of electricity, satisfaction and user-side fluctuation degree are taken into comprehensive account. An improved adaptive weight multi-objective particle swarm optimization (IAW-MOPSO) algorithm is proposed to realize the scheduling optimization of household power load. The local improvement ability and global search ability of particle swarm optimization are balanced by updating the inertia weight of particle fitness value. The simulation results of five groups show that the proposed optimization strategy reduces the electricity charge by 29%, ensures the stability of electricity consumption in the peak period, and …
An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen
An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen
Journal of System Simulation
Abstract: During the COVID-19 pandemic, supply chain of manufacturing companies is facing more severe product demand uncertainty, which is manifested in the sharp increase in demand for certain types of products and the increased fluctuations in supply for raw materials. For this supply chain optimization problem with demand uncertainty, a multi-objective stochastic programming model is developed in order to maximize the total profit and product order fulfillment rate simultaneously in this paper. For solving the investigated problem, a new evolutionary multi-objective simulation optimization algorithm is proposed by combining the mechanism of NSGA-II and simulation computing budget allocation adaptively. Experimental …
Augmenting The Space Domain Awareness Ground Architecture Via Decision Analysis And Multi-Objective Optimization, Albert R. Vasso, Richard G. Cobb, John M. Colombi, Bryan D. Little, David R. Meyer
Augmenting The Space Domain Awareness Ground Architecture Via Decision Analysis And Multi-Objective Optimization, Albert R. Vasso, Richard G. Cobb, John M. Colombi, Bryan D. Little, David R. Meyer
Faculty Publications
Purpose — The US Government is challenged to maintain pace as the world’s de facto provider of space object cataloging data. Augmenting capabilities with nontraditional sensors present an expeditious and low-cost improvement. However, the large tradespace and unexplored system of systems performance requirements pose a challenge to successful capitalization. This paper aims to better define and assess the utility of augmentation via a multi-disiplinary study. Design/methodology/approach — Hypothetical telescope architectures are modeled and simulated on two separate days, then evaluated against performance measures and constraints using multi-objective optimization in a heuristic algorithm. Decision analysis and Pareto optimality identifies a set …
Efficiently Estimating Survival Signature And Two-Terminal Reliability Of Heterogeneous Networks Through Multi-Objective Optimization, Daniel Bruno Lopes Da Silva
Efficiently Estimating Survival Signature And Two-Terminal Reliability Of Heterogeneous Networks Through Multi-Objective Optimization, Daniel Bruno Lopes Da Silva
Graduate Theses and Dissertations
The two-terminal reliability problem is a classical reliability problem with applications in wired and wireless communication networks, electronic circuit design, computer networks, and electrical power distribution, among other systems. However, the two-terminal reliability problem is among the hardest combinatorial problems and is intractable for large, complex networks. Several exact methods to solve the two-terminal reliability problem have been proposed since the 1960s, but they have exponential time complexity in general. Hence, practical studies involving large network-type systems resort to approximation methods to estimate the system's reliability. One attractive approach for quantifying the reliability of complex systems is to use signatures, …
Multi-Objective Optimization Of Multi-Task Parallel Motorcycle Suspension System Parameters, Xiansheng Ran, Yang Jing, Luo Ling, Chen Kai
Multi-Objective Optimization Of Multi-Task Parallel Motorcycle Suspension System Parameters, Xiansheng Ran, Yang Jing, Luo Ling, Chen Kai
Journal of System Simulation
Abstract: Aiming at the comprehensive problem of wobble of front suspension system and weave of rear suspension system of large displacement motorcycle at medium and high speed, a multi-objective optimization scheme based on sensitivity analysis and approximate modeling is proposed. The motorcycle model is established and the dynamics simulation is carried out. The lateral acceleration of front wheel's centroid position, the yaw rate and roll rate of whole vehicle's centroid position, which characterize the wobble and weave are the targets. The sensitivity analysis of suspension system parameters and the approximate modeling are carried out. Based on the analysis results, …
Combined Gearbox Transmission Ratio Optimization Research Based On Hybrid Particle Swarm, Runhong Wang, Hongjun Wang, Xiangjun Zou, Zeqin Zeng, Li Hui, Zhaofeng Huang, Weiliang Liu
Combined Gearbox Transmission Ratio Optimization Research Based On Hybrid Particle Swarm, Runhong Wang, Hongjun Wang, Xiangjun Zou, Zeqin Zeng, Li Hui, Zhaofeng Huang, Weiliang Liu
Journal of System Simulation
Abstract: Aiming at the difficulty to obtain the optimal solution for the transmission ratio distribution of combined transmission, an optimization method for the transmission ratio of the combined multi-speed transmission based on the hybrid particle swarm optimization algorithm is proposed. Based on the multi-objective particle swarm algorithm, a leader population with a self-renewal mechanism is introduced to form a hybrid particle swarm algorithm. A multi-objective optimization model is established by taking the transmission ratio of each stage of single-speed transmission as a variable, combining the transmission chain layout, taking the driving power loss rate, specific fuel consumption loss …
Defensive Counterair For Air Base Air Defense Using Directed Energy And Kinetic Energy Weapons, Andrew S. Wilson
Defensive Counterair For Air Base Air Defense Using Directed Energy And Kinetic Energy Weapons, Andrew S. Wilson
Theses and Dissertations
Air bases in key locations provide a strategic advantage to the countries that access them, and are at constant threat from adversaries. This research seeks to determine the optimal maneuvering of a fixed number of fighter aircraft in a combat air patrol for defensive counterair to maximally and effectively attrit the inbound cruise missile threat to a stationary high value asset such as an air base. The problem formulation identifies multiple objectives for the model: minimize the distance traveled for the fighters, minimize the time utilized to engage the incoming cruise missiles, and maximize the number of cruise missiles destroyed. …
Collaborative Optimization Of Production And Energy Consumption In Flexible Workshop, Ding Yu, Wang Yan, Zhicheng Ji
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 …
Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He
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 …
Dynamic Environmental And Economic Dispatching Of Wind Farm Based On Multi-Objective, Le Wei, Xijin Li
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 …
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
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
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 …
3d Printing Orientation Optimization Based On Non-Dominated Sorting Genetic Algorithm, Dai Ning, Lisong Ou, Renkai Huang, Liu Hao
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
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
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
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
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
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
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 …
Moea/D Algorithm Based On The Hybrid Framework For Multi-Objective Evolutionary Algorithm, Hongjun Tian, Wang Lei, Qidi Wu
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 …