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A hybrid Ant Colony and Cuckoo Search algorithm for Route Optimization of Heating Engineering

ENERGIES 2018年第10期11卷

作者： Zhang, Yang Zhao, Huihui Cao, Yuming Liu, Qinhuo Shen, Zhanfeng Wang, Jian Hu, Minggang North China Power Engn Co Ltd China Power Engn Consulting Grp Beijing 100120 Peoples R China Chinese Acad Sci Inst Remote Sensing & Digital Earth State Key Lab Remote Sensing Sci Beijing 100101 Peoples R China Beijing Univ Civil Engn & Architecture Sch Geomat & Urban Spatial Informat Beijing 100044 Peoples R China

The development of remote sensing and intelligent algorithms create an opportunity to include ad hoc technology in the heating route design area. In this paper, classification maps and heating route planning regulations are introduced to create the fitness function. Modifications of ant colony optimization and the cuckoo search algorithm, as well as a hybridization of the two algorithms, are proposed to solve the specific Zhuozhou-Fangshan heating route design. Compared to the fitness function value of the manual route (234.300), the best route selected by modified ant colony optimization (ACO) was 232.343, and the elapsed time for one solution was approximately 1.93 ms. Meanwhile, the best route selected by modified Cuckoo Search (CS) was 244.247, and the elapsed time for one solution was approximately 0.794 ms. The modified ant colony optimization algorithm can find the route with smaller fitness function value, while the modified cuckoo search algorithm can find the route overlapped to the manual selected route better. The modified cuckoo search algorithm runs more quickly but easily sticks into the premature convergence. Additionally, the best route selected by the hybrid ant colony and cuckoo search algorithm is the same as the modified ant colony optimization algorithm (232.343), but with higher efficiency and better stability.

关键词： heating engineering route planning ant colony optimization cuckoo search hybrid intelligent algorithm

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Fuzzy multi-objective chance-constrained programming model for hazardous materials transportation

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INTERNATIONAL JOURNAL OF GENERAL SYSTEMS 2016年第3期45卷 286-310页

作者： Du, Jiaoman Yu, Lean Li, Xiang Beijing Univ Chem Technol Sch Econ & Management Beijing 100029 Peoples R China

Hazardous materials transportation is an important and hot issue of public safety. Based on the shortest path model, this paper presents a fuzzy multi-objective programming model that minimizes the transportation risk to life, travel time and fuel consumption. First, we present the risk model, travel time model and fuel consumption model. Furthermore, we formulate a chance-constrained programming model within the framework of credibility theory, in which the lengths of arcs in the transportation network are assumed to be fuzzy variables. A hybrid intelligent algorithm integrating fuzzy simulation and genetic algorithm is designed for finding a satisfactory solution. Finally, some numerical examples are given to demonstrate the efficiency of the proposed model and algorithm.

关键词： Hazardous materials transportation multi-objective programming fuzzy chance-constrained programming hybrid intelligent algorithm

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Order acceptance and scheduling problem with outsourcing in seru production system considering lot-spitting

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EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING 2022年第1期16卷 91-116页

作者： Wang, Lili Zhang, Zhe Yin, Yong Nanjing Univ Sci & Technol Sch Econ & Management Nanjing 210094 Peoples R China Doshisha Univ Grad Sch Business Kamigyo Ku Kyoto 6028580 Japan

This paper focuses on the order acceptance and scheduling problem considering lot-spitting with outsourcing decisions simultaneously in seru production system. Assume that the company's production capacity is limited, and that the outsourcer will require different outsourcing costs for different orders. Therefore, when the outsourcing cost of an order is relatively high, the company can choose to process it internally or reject the order directly, so that the company can achieve higher revenue. To solve this complex problem, a mixed 0-1 integer programming model is established, and the objective function maximisation of the net revenue is considered. Due to the complexity of the problem and model, an efficient hybrid algorithm named adaptive simulated annealing genetic algorithm (ASAGA) is designed for the proposed model. Finally, the experimental results show that the ASAGA has better optimal results and excellent scalability. [Received: 27 August 2019;Accepted: 6 February 2021]

关键词： order acceptance and scheduling OAS seru outsourcing lot-spitting hybrid intelligent algorithm

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A multiobjective integrated procurement, production, and distribution problem of supply chain network under fuzziness

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IFAC-PapersOnLine 2021年第1期54卷 1104-1111页

作者： K. Douaioui M. Fri C. Mabrouki E.A. Semma Hassan First University of Settat Faculté Sciences et Technique BP 577 Settat Morocco Euromed Institute of Technology (EIT). Euro-Med University of Fes (UEMF) Route de Meknes Fès 3007 Morocco

In this paper, we devoted the integration problem of procurement, production and distribution of a supply chain network under uncertainty within the credibility framework. The proposed model is a mixed integer linear programming which takes into account technological constraints arising in many kinds of supply chain network and aims to minimize the total costs such as production, storage, and distribution. Besides, the objective function coefficients (e.g. production cost, inventory holding and transport costs) and other parameters (e.g., demand, and production capacity) are all considered fuzzy numbers. To solve the proposed model a hybrid intelligent algorithm is designed based on genetic algorithm and fuzzy simulation. Finally, reported numerical results show the practicality of the proposed model.

关键词： Supply Chain Network Credibility Theory Expected Value Model hybrid intelligent algorithm

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Three types of models for stochastic scheduling with fuzzy information

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Journal of Statistics and Management Systems 2003年第3期6卷 493-504页

In this paper we consider the scheduling problems on a single machine in random fuzzy environments. Three types of random fuzzy programming models are provided for single machine scheduling with random fuzzy processing times. A hybrid intelligent algorithm is designed to solve the proposed models and its effectiveness is illustrated by numerical experiments.

关键词： Scheduling single machine random fuzzy programming hybrid intelligent algorithm

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Integrated Planning of Distribution Systems with Distributed Generation and Demand Side Response

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Energy Procedia 2015年 75卷 981-986页

作者： Haoyong Chen Zengyu Wang Haifeng Yan Haobin Zou Bo Luo School of Electric Power South China University of Technology Wushan RD. Tianhe DistrictGuangzhou 510641 P.R.China Asia-Pacific Research Institute of Smart Grid and Renewable Energy Kowloon Hong Kong Qingyuan Power Sypply Bureau Guangdong Power Grid Cooperation

The planning and operational issues of distribution systems have attracted more and more attentions from researchers with the development of Smart Grids. A new integrated planning model of distribution systems and the solution methods are proposed in this paper to investigate the way of improving the economy and reliability of distribution system planning by making full use of distributed generation (DG) and demand side response (DSR) resources. The planning objective function is formed by taking consideration of the investment and operation cost of DG, transmission loss cost, compensation cost for interruptible loads, purchasing electricity cost, and the environmental benefits after integration of DG. The integrated planning scheme will be acquired by introducing price induced interruptible load to distribution system planning model. A hybrid intelligent algorithm consisting of support vector machines (SVM) and particle swarm optimization algorithm (PSO) is proposed to solve the integrated planning model. The effectiveness and advantages of the model and algorithms and the necessity of considering the demand side resources are verified by simulation cases based on a real regional distribution system in China.

关键词： Distribution network planning integrated planning distributed generation demand side response hybrid intelligent algorithm

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Flow-Shop Scheduling Models with Parameters Represented by Rough Variables

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Tsinghua Science and Technology 2003年第1期8卷 55-59页

作者：彭锦 Kakuzo Iwamura Department of Mathematical Sciences State Key Laboratory of Intelligent Technology and Systems Tsinghua University Department of Mathematics Josai University

In reality, processing times are often imprecise and this imprecision is critical for the scheduling procedure. This research deals with flow-shop scheduling in rough environment. In this type of scheduling problem, we employ the rough sets to represent the job parameters. The job processing times are assumed to be rough variables, and the problem is to minimize the makespan. Three novel types of rough scheduling models are presented. A rough simulation-based genetic algorithm is designed to solve these models and its effectiveness is well illustrated by numerical experiments.

关键词： scheduling flow-shop rough set rough simulation rough programming hybrid intelligent algorithm

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Continuous Space Wireless Communication Tower Placement by hybrid Simulated Annealing

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FUTURE INTERNET 2024年第4期16卷

作者： Tang, Maolin Li, Wei Queensland Univ Technol Sch Comp Sci Brisbane Qld 4000 Australia Cent Queensland Univ Sch Engn & Technol Rockhampton Qld 4702 Australia

Wireless communication tower placement arises in many real-world applications. This paper investigates a new emerging wireless communication tower placement problem, namely, continuous space wireless communication tower placement. Unlike existing wireless communication tower placement problems, which are discrete computational problems, this new wireless communication tower placement problem is a continuous space computational problem. In this paper, we formulate the new wireless communication tower placement problem and propose a hybrid simulated annealing algorithm that can take advantage of the powerful exploration capacity of simulated annealing and the strong exploitation capacity of a local optimization procedure. We also demonstrate through experiments the effectiveness of this hybridization technique and the good performance and scalability of the hybrid simulated annulling in this paper.

关键词： communication tower placement optimization algorithm simulated annealing hybrid intelligent algorithm

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Research on Fuzzy Multi-objective Multi-period Portfolio by hybrid Genetic algorithm with Wavelet Neural Network

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ENGINEERING LETTERS 2020年第2期28卷 594-600页

作者： Yu, Yechun Deng, Xue Chen, Chuangjie Cheng, Kai South China Univ Technol Sch Software Engn Guangzhou 510006 Peoples R China South China Univ Technol Sch Math Guangzhou 510640 Peoples R China Shenzhen Yun Zhong Fei Network Technol Co Ltd Shenzhen 518057 Peoples R China

This paper deals with fuzzy multi-objective multi-period portfolio selection problems. The portfolio selection is proposed by taking into account three criteria of final return, cumulative risk and entropy. In the model, the return level is quantified by the possibilistic mean value of return, and the risk is quantified by the possibilistic variance of return while fuzzy entropy is adopted to increase the risk dispersion degree to some extent. Then a fuzzy multi-objective multi-period portfolio model is presented in a more complex market environment. To solve the complex model, the multi-objective functions are transformed into a single objective and the risk preference parameter is introduced to balance the return and risk to meet with investors' preferences. To ensure the investor can obtain the optimal portfolio strategy, a hybrid intelligent algorithm is designed by combining both genetic algorithm and wavelet neural network algorithm, which not only utilizes the good localization property of wavelet transform but also utilizes the effective self-learning function of neural network. Finally, a numerical example is presented to illustrate this approach and the designed algorithm. The results show that the proposed model and the designed algorithm are practical and flexible, while they are meaningful for the study on portfolio selection and multi-objective programming.

关键词： portfolio selection multi-period multi-objective entropy hybrid intelligent algorithm

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Design and implementation of optimal algorithm for shelves handling based on the change of return position of movable shelves

ENGINEERING REPORTS

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ENGINEERING REPORTS 2024年第5期6卷

作者： Yao, Wenbin Gong, Gaiyun Zhejiang Tech Inst Econ Hangzhou 310028 Peoples R China Hangzhou Dianzi Univ Sch Sci Hangzhou Peoples R China

A shelf-to-person picking system based on automatic guided vehicles (AGVs) is developed in the mobile shelf warehouse, which can meet the needs of multi batches, small volume and multi variety picking. In this system, the efficiency of picking is affected by Storage location allocation, optimal combination of picking orders, optimization of handling shelves and AGVs scheduling. This article establishes a mathematical model according to the shortest walking distance of AGV in view of the situation that the return position of the shelf can be changed. In this article, a hybrid intelligent algorithm is designed, and its effectiveness is verified by numerical examples. At the same time, the heuristic algorithm and intelligent algorithm were compared in two cases, and the range of intelligent algorithm parameters was analyzed to verify the stability and effectiveness of the algorithm.

关键词： AGVs change of return position hybrid intelligent algorithm shelf handling optimization shelf-to-person

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