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Bi-objective covering tour location routing problem with replenishment at intermediate depots: Formulation and meta-heuristics

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COMPUTERS & INDUSTRIAL ENGINEERING 2017年 110卷 191-206页

作者： Nedjati, Arman Izbirak, Gokhan Arkat, Jamal Eastern Mediterranean Univ Dept Ind Engn Via Mersin 10 Famagusta North Cyprus Turkey Univ Kurdistan Dept Ind Engn Pasdaran Blvd Sanandaj Iran

The Covering tour Location Routing Problem with Replenishment at intermediate depots (CLRPR) is an extension of location routing problem with service time restriction, replenishment at intermediate depots, and customer mobility in a predefined walking distance. Among the different applications of the problem, this study concentrates on the post-earthquake relief distribution system. This paper represents a new bi-objective integer linear programming model that minimizes the total weighted waiting time and the total amount of lost demands. The mathematical model is coded in GAMS software and solved optimally by Cplex solver with epsilon-constraint method. In order to cope with the NP-hardness feature of the problem, the nsgaii multi-objective algorithm with two distinct improvements are proposed as heuristic solution procedures. The results of 36 randomly generated test problems were analyzed in terms of quality, quantity, diversity and spread of Pareto front solutions. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Location routing problem Humanitarian logistics Intermediate facility nsgaii algorithm

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Fuzzy multi-objective location and routing problem

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第3期39卷 3259-3273页

作者： Shahsavari-Pour, Nasser Bahram-Pour, Najmeh Kazemi, Mojde Vali E Asr Univ Dept Ind Management Rafsanjan Iran Alzahra Univ Dept Ind Engn Tehran Iran Shahid Bahonar Univ Dept Ind Engn Kerman Iran

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index;the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

关键词： Fuzzy optimization location and routing firefly algorithm nsgaii algorithm reliability failure

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Comparative research of optimization algorithms for parameters calibration of watershed hydrological model

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2016年第3期16卷 653-669页

作者： Huo, Jiuyuan Liu, Liqun Zhang, Yaonan Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Gansu Peoples R China Gansu Agr Univ Coll Informat Sci & Technol Lanzhou Gansu Peoples R China Chinese Acad Sci Cold & Arid Reg Environm & Engn Res Inst Lanzhou Gansu Peoples R China Gansu Data Engn & Technol Res Ctr Resources & Env Lanzhou Gansu Peoples R China

Parameter optimization and calibration of the hydrological model has been one of the important research fields in hydrological forecasting. This paper is written to address the inherent defects that traditional parameter optimization of Xinanjiang hydrological model with a single objective entails. These methods cannot fully exploit hydrological characteristics information from hydrological observation. We selected the Nash Sutcliffe coefficient, which is known to be biased for high flows and the logarithmic form of the Nash Sutcliffe coefficient that emphasize low-flow values as the objective functions. Then, we adopted the multi-objective optimization algorithms, such as the Nondominated Sorted Genetic algorithm-II (nsgaii) and the Third Evolution Step of Generalized Differential Evolution (GDE3), and the single-objective optimization algorithm, Simulated Annealing (SA). These algorithms were applied in Heihe River Basin to calibrate parameters of the Xinanjiang hydrological model for long-term prediction of river discharges. Through the evaluation of the Pareto optimal parameter set derived from multi-objective optimization algorithms and the optimal solution obtained from the single objective algorithm, the results showed that the multi-objective optimization algorithms, in particular the NSGA-II algorithm, perform best to locate the Pareto optimal solutions in the parameter search space. They can also obtain better results with respect to the model parameters calibrated by the single objective algorithm. The major contribution of this work is the comparative application research of single-objective optimization with the multi-objective optimization algorithms for the parameters optimization of the Xinanjiang model in the Heihe River basin.

关键词： Hydrological model parameter calibration multi-objective optimization algorithm Xinanjiang model nsgaii algorithm GDE3 algorithm SA algorithm

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Intelligent Personalized E-Learning Platform using Evolutionary algorithms 8

Intelligent Personalized E-Learning Platform using Evolution...

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8th International Conference on ICT & Accessibility (ICTA)

作者： Soui, Makram Saudi Elect Univ Coll Comp & Informat Riyadh Saudi Arabia Univ Manouba Artificial Intelligence Res Unit Manouba Tunisia

ISBN: (纸本)9781665466417

The aim of adaptive learning is to personalize the structure of course content according to the learner profiles. The idea is to propose a suitable learning resource for the student. In this work, we study the efficiency of evolutionary algorithms to generate a rule-based model for course personalization. In fact, we consider the course personalization as a search-based optimization problem where the goal is to maximize the accuracy of recommended learning resources and to minimize the complexity of the generated individual. We conducted a comparative study of four multi-objective evolutionary algorithms (nsgaii, IBEA, PESA2, SPEA2) in terms of their efficiency. The obtained results confirm the efficiency of the nsgaii algorithm to extract appropriate personalization rules for course adaptation. The obtained results prove the efficiency of the rule- based model with 93% of accuracy rate.

关键词： Personalized e-learning rule-based model evolutionary algorithm nsgaii algorithm

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Multi-objective Worker Assignment Planning Model and algorithm Considering Worker Flexibility and Cooperation 22

Multi-objective Worker Assignment Planning Model and Algorit...

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22nd IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD)

作者： Wang, Yiqi Zhang, Xiaodong Liu, Suhui Univ Sci & Technol Beijing Donglinks Sch Econ & Management Beijing Peoples R China

ISBN: (纸本)9781538614822

The worker assignment problem is of great importance in high-variety, small-quantity workshop production systems. This paper presents a cooperative worker assignment model by introducing a flexible worker cooperation strategy and multi-objective optimization to minimize the makespan and maximum worker load and total worker load. To solve the model, an improved nsgaii algorithm is designed, which brings about improvement to the method of selection and trim operation. Then, the contrast experiments of the model and algorithm were carried out and the results show that the cooperative worker assignment model is more competent with the makespan and maximum worker load of the workshop and more assignment scheduling plans will be obtained. In addition, the improved algorithm can effectively avoid local optimization during the calculation process.

关键词： Worker assignment nsgaii algorithm worker cooperation worker flexibility

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Design and optimization of PMSM with outer rotor for electric vehicle 12

Design and optimization of PMSM with outer rotor for electri...

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International Multi-Conference on Systems, Signals and Devices (SSD)

作者： Msaddek, Hejra Brisset, Stephane Mansouri, Ali Trabelsi, Hafedh Engn Sch Sfax CES Lab Sfax Tunisia Cent Sch Lille L2EP Lab Lille France

ISBN: (纸本)9781479917587

In this paper, the importance of electrical machine was involved. So researches are oriented to make a progress in this domain. Permanent magnet synchronous machine (PMSM) is selected to be studied in this work. Two optimization methods are used in the design of the PMSM for the application of in wheel motor of electric cars. The first one is sequential quadratic programming (SQP) algorithm using the interface Sophemis developed in L2EP laboratory which is a deterministic method and the second is nsgaii algorithm which is a stochastic method. Finally, a comparison between the two methods, using pareto front, is discussed and the appropriate one is then choosed.

关键词： In-wheel motor design optimization epsilon-constraint method SQP algorithm nsgaii algorithm

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An Analysis of Increasing the Purity of Ethylene Production in the Ethylene Fractionation Column by the Genetic algorithm

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CHEMICAL PRODUCT AND PROCESS MODELING 2020年第3期15卷

作者： Karimi, Asadollah Soltani, Hadi Hasanzadeh, Aydin Univ Maragheh Dept Chem Engn Fac Engn Maragheh Iran Islamic Azad Univ Ahar Branch Dept Chem Engn Ahar Iran

Distillation columns are among the most common fractionation systems with numerous applications in petrochemical units. Hence, the optimization of these columns is a large step in reducing energy consumption and increasing process productivity. This study was, therefore, carried out as a case study of the simulation and optimization of the parameters influencing the ethylene production of the ethylene distillation column in an olefin unit. The two defined objective functions in this research were maximum mass flow of ethylene in the upstream flow of the distillation column and the minimum energy consumption in the distillation column. The optimal operating conditions for the independent variables were estimated using the nsgaii algorithm. The sensitivity analysis of the results was, thereafter, carried out and the optimization results introduced tray no. 71 as the most suitable feed location. In addition, the optimal reflux ratio and the optimal feed flow temperature were 5.26 and -18.49 degrees C, respectively. In this condition, the upstream ethylene flow rate and energy consumption in the unit increased by approximately 0.74 % and 0.9 % as compared to the initial conditions, respectively.

关键词： ethylene distillation columns nsgaii algorithm simulation

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Presenting a mathematical model of blood supply chain considering the efficiency of collection centers and development of metaheuristic algorithm in M/M/C/K queuing system (vol 34, bhae012, 2024)

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CEREBRAL CORTEX 2024年第3期34卷 bhae012-bhae012页

作者： Karamipour, Meysam Kerman, Mehrdad Agha Mohammad Ali Iran University of Science and Technology School of Management Economics and Progress Engineering Iran

In this study, a multiobjective model was devoted to the objectives of minimizing blood supply chain costs and minimizing the waiting time of blood donors for blood transfusion and minimizing blood transfusion schedule and increasing the efficiency of fixed and mobile centers in collecting blood. One of the most important constraints considered in the mathematical model is the capacity constraints of considering fixed and mobile blood facilities and management of the transfer of blood products to centers for collecting and distinguishing healthy and unhealthy blood. A multiobjective model was considered with the objectives of minimizing blood supply chain costs, the waiting time of blood donors for blood transfusion, and blood transfusion timing and increasing the efficiency of fixed and mobile centers in blood collection. The model findings were analyzed in order to validate the model on a larger scale, using the meta-innovative algorithm nsgaii and MOSPO. According to the research findings, we suggest that fuzzy uncertainty and fair distribution problem shouldn’t be added to the dimensions of the main problem, and further analysis should be done in this area. It was shown that the nsgaii algorithm’s performance was better than the MOPSO meta-heuristic algorithm.

关键词： queueing system nsgaii algorithm nonlinear programming supply chain

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A New Multi-objective Multi-mode Model for Optimizing EPC Projects in Oil and Gas Industry

A New Multi-objective Multi-mode Model for Optimizing EPC Pr...

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International Conference Image Processing, Computers and Industrial Engineering (ICICIE’2014, Kuala Lumpur)

作者： Vida Arabzadeh Hassan Haleh S.M.R.Khalili Department of Industrial & Mechanical Engineering Qazvin BranchIslamic Azad University Industrial Engineering Dept. Islamic Azad UniversityQazvin Branch Faculty of Mechanical Engineering K.N.Toosi University of Technology

the objective of this paper is implementing optimization method to investigate time,cost and quality trade off in engineering and construction stages of an EPC *** first step is to describe the results of research that has been conducted on optimization of grid composite structure used as grating system for platform in petrochemical equipment by using Multi Objective Genetic algorithms(nsgaii) and Artificial Neural Networks(ANN).ANN is trained data sets taken from numerical analyses spread randomly over the design *** trained network is then used to predict the values of the constraint function(performance and Cost).Then by using nsgaii the grid composite structure cost and performance are minimized simultaneously for a variety of geometrical and material variables.A set of near-optimum(in a Pareto sense) configurations is determined respectively.A platform fabrication stage is also considered for trading time and cost off by using nsgaii as second part of *** study shows the ability of optimizing algorithms in EPC projects to minimize cost and time regarding to performance and *** applied method in this paper has been implemented successfully in real EPC project for construction grating system of petrochemical equipment.

关键词： Cost Neural network nsgaii algorithm grid composite structure trade off project scheduling

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