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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Li, Ling Liu, Min Shen, Weiming Cheng, Guoqing Tongji Univ Sch Elect & Informat Engn Shanghai Peoples R China Jingdezhen Ceram Inst Sch Informat Engn Jingdezhen Peoples R China

ISBN: (纸本)9781509018970

Motivated by the challenges of seeking the optimal E-business based maintenance, repair and overhaul (E-MRO) service policy, simultaneously considering bilateral requirements of quality of service (QoS), this paper presents a mathematical model based on variable fuzzy recognition and multi-objective programming. Cloud model is utilized to quantify the information of bilateral requirements as the numerical values. Then, the comprehensive satisfaction of multiple attribute is calculated by using variable fuzzy recognition method. Based on bilateral satisfactions, a multi-objective programming model is formulated, where bilateral QoS satisfactions are modeled as objective functions. By using global criteria method, the multi-objective optimization is transformed to an equivalent single objective optimization, which can be solved by LINGO. Finally, the optimal E-MRO service policy satisfying bilateral requirements is obtained. A case study illustrated the feasibility and efficiency of the proposed model.

关键词： E-MRO service policy bilateral requirements variable fuzzy recognition multi-objective programming

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Mixed Duality of multi-objective programming Involving a Kind of Generalized Convexity 12

Mixed Duality of Multi-Objective Programming Involving a Kin...

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12th International Conference on Computational Intelligence and Security (CIS)

作者： Li, Xiangyou Yannan Univ Coll Math & Comp Sci Yannan 716000 Shaanxi Peoples R China

In this paper, new classes of generalized convex functions are introduced for non-smooth multi -objective programming problem, mixed type dual problem is established, weak, strong duality theorems are derived under ne... 详细信息

ISBN: (纸本)9781509048403

关键词： generalized convex function multi-objective programming mixed duality non-smooth

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Fuzzy multi-objective programming algorithm for vehicle routing problems with backhauls

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EXPERT SYSTEMS WITH APPLICATIONS 2015年第13期42卷 5632-5644页

作者： Yalcin, Gulcin Dinc Erginel, Nihal Anadolu Univ Fac Engn Dept Ind Engn TR-26555 Eskisehir Turkey

The vehicle routing problem with backhauls (VRPB) is an extension of the standard vehicle routing problem. VRPB has two sets of customers: linehaul customers and backhaul customers. The aim of this study is to propose a new algorithm based on fuzzy multi-objective programming (FMOP-VRPB algorithm) to solve the VRPB. The FMOP-VRPB algorithm has three phases;clustering, routing and local search. In the clustering phase, customers are assigned to vehicles by the proposed multi-objective programming (MOP) model with two objective functions: minimizing the total distance and maximizing the total savings value. The proposed MOP model is solved by fuzzy operators. The weights of the objectives are also calculated by a fuzzy two-person zero-sum game with mixed strategies using membership functions in a fuzzy pay-off matrix. In the routing phase, each vehicle is routed as a traveling salesman problem with backhauls. The local search phase is used to improve the routes. The primary contributions of the FMOP-VRPB algorithm are to consider the two objectives, to determine the weights of objectives using the proposed fuzzy pay-off matrix in the clustering phase and to use only mathematical programming in both the clustering and routing phases through many customers in an acceptable CPU time. The algorithm will also show that the proposed MOP model defines the seed customers itself in the clustering phase and will always generates feasible clusters, contrary to the reports in the literature. Benchmark problems from the literature are solved to test the performance of the FMOP-VRPB algorithm. The results indicate that the FMOP-VRPB algorithm generates sufficient solutions, and CPU times are within acceptable limits. In addition, a weekly routing problem for a logistics department of a ceramics firm in Turkey is solved by the FMOP-VRPB algorithm. Additionally, this study is the first to solve a real world VRPB;the solution shows that the FMOP-VRPB algorithm is suitable and effectiv

关键词： Vehicle routing problems with backhauls multi-objective programming Fuzzy approach Fuzzy pay-off matrix

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Mixed Duality of multi-objective programming Involving a Kind of Generalized Convexity

Mixed Duality of Multi-Objective Programming Involving a Kin...

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International Conference on Computational Intelligence and Security

作者： Xiangyou Li College of Mathematics and Computer Science Yann'an University Yann'an Shaanxi China

In this paper, new classes of generalized convex functions are introduced for non-smooth multi-objective programming problem, mixed type dual problem is established, weak, strong duality theorems are derived under new... 详细信息

ISBN: (纸本)9781509048410

In this paper, new classes of generalized convex functions are introduced for non-smooth multi-objective programming problem, mixed type dual problem is established, weak, strong duality theorems are derived under new convexity.

关键词： non-smooth generalized convex function multi-objective programming mixed duality

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Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach

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ANNALS OF OPERATIONS RESEARCH 2015年第1期234卷 57-76页

作者： Li, Jianping Sun, Xiaolei Wang, Fei Wu, Dengsheng Chinese Acad Sci Inst Policy & Management Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

Optimization of oil-imports portfolio has attracted considerable attention from corporate operators as well as government and its strategic planners. This paper proposes a methodology of oil-importing portfolio optimization based on the fundamental process of intelligent knowledge management (IKM). Centering on the maritime system, optimal solutions are derived for different risk scenarios. Specifically, three main steps are involved: formulating a multi-objective programming (MOP) model, integrating the composite risk exposure with domain knowledge, as well as knowledge acquisition on risk scenarios and influence of transportation risk. For illustration, optimization of the maritime structure of China's oil imports is performed to verify the practicability of the novel methodology. Experimental results suggest that the risk-adjusted factors' augmentation can spread the risk wider and eventually enhance risk optimization capability in the MOP model. With a given risk-adjusted factor, the influence of transportation risk on an optimal plan is simulated and analyzed. The paper uses the fundamental IKM process for transforming the data (rough knowledge) into intelligent knowledge (transformation from T1 to T2) in the empirical study on risk integration and optimization of oil-importing maritime system. It is helpful to explore hidden patterns. What's more, results suggest that it is necessary to highlight the influence of transportation risk in order to support decision makers from different domains to obtain more reasonable optimal solutions.

关键词： Risk integration Country risk Transportation risk Intelligent knowledge management multi-objective programming

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E-MRO Service Policy with Bilateral Requirements using Variable Fuzzy Recognition and multi-objective programming

E-MRO Service Policy with Bilateral Requirements using Varia...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Ling Li Weiming Shen Min Liu Guoqing Cheng School of Electronic and Information Engineering Tongji University Shanghai P.R. China School of Information Engineering Jingdezhen Ceramic Institute Jingdezhen P.R. China

ISBN: (纸本)9781509018987

Motivated by the challenges of seeking the optimal E-business based maintenance, repair and overhaul (E-MRO) service policy, simultaneously considering bilateral requirements of quality of service (QoS), this paper presents a mathematical model based on variable fuzzy recognition and multi-objective programming. Cloud model is utilized to quantify the information of bilateral requirements as the numerical values. Then, the comprehensive satisfaction of multiple attribute is calculated by using variable fuzzy recognition method. Based on bilateral satisfactions, a multi-objective programming model is formulated, where bilateral QoS satisfactions are modeled as objective functions. By using global criteria method, the multi-objective optimization is transformed to an equivalent single objective optimization, which can be solved by LINGO. Finally, the optimal EMRO service policy satisfying bilateral requirements is obtained. A case study illustrated the feasibility and efficiency of the proposed model.

关键词： multi-objective programming E-MRO service policy bilateral requirements variable fuzzy recognition

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The influence of multi objective programming on Aerobics Teaching

The influence of multi objective programming on Aerobics Tea...

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2017 International Conference on Advanced Education,Psychology and Sports Science(AEPSS 2017)

作者： Yali Xu Kaihua Xu School of Physical Education Jiangxi University Of Traditional Chinese Medicine Police Training Management Department Jiangxi People's Police College

This paper explore application method of multi-objective programming and discussed its effect in aerobics teaching, through the analysis of the summary of multi-objective programming, studies the principles that need ... 详细信息

关键词： multi-objective programming Aerobics Teaching Impact

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A multi-objective Stochastic programming Approach for Project Time, Cost and Quality Trade-off Problem (TCQTP)

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JORDAN JOURNAL OF CIVIL ENGINEERING 2016年第4期10卷 553-563页

作者： Ahadian, Behrooz Veisy, Omid Azizi, Vahid Islamic Azad Univ Dept Ind Engn Najaf Abad Branch Esfahan Iran Univ Tehran Dept Ind Engn Tehran Iran Khajeh Nasir Toosi Univ Technol Fac Ind Engn Tehran Iran

Generally, in project time, cost and quality trade-off problems, the decision maker (DM) has to take different conflicting objectives into account in order to find an optimal solution. In project management literature, many models have been developed for project crashing and project time-cost trade-off, but only a few of them consider quality as an objective. This article employs a chance constrained compromise programming approach (CCCP) to solve the time, cost and quality trade-off problem (TCQTP). The purpose of this paper is to present and test a new model for the project time, cost and quality problem. In fact, we try to find the optimal decrease in cost and duration of activities while maximizing quality under uncertainty conditions. In order to expect more realistic outcomes for the problem of uncertainties in project activities, time should be taken into account. Therefore, we assume the activity duration as a random and normally distributed parameter. An example of a project network, consisting of 6 nodes and 7 activities, is analyzed under different uncertainty levels.

关键词： Project management Chance-constrained compromise programming multi-objective programming Time cost and quality trade-off Linear programming

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A New Approach to multi-objective programming based on Satisfied Degree under Fuzzy Environment 10

A New Approach to Multi-objective Programming based on Satis...

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10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)

作者： Jie, Jingduo Li, Fachao Jin, Chenxia Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang Peoples R China

ISBN: (纸本)9781467393232

Fuzziness is a common uncertainty who exists widespread in decision process and how to process fuzziness is a widespread context in academic and application fields. For the multi-objective programming under fuzzy environment, this paper firstly analyze the essential characteristics of fuzzy objectives. Then fuzzy objectives are divided into three kinds and represent by fuzzy number by introducing deviation parameter a. Then, regarding membership of fuzzy number as the satisfied degree, we establish the multi-objective programming based on satisfied degree (denotes as MP-SD) and a new solving strategy based on MP-SD is further given. Finally, we illustrate the validity of MPSD through a case. The analytical results show that the proposed approach is effective in fuzzy decision environment and provide rich decision theories for integrated multi-objective programming problems in artificial intelligence and resource management and so on.

关键词： multi-objective programming satisfied degree fuzzy environme deviation parameter decision making

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Dynamic virtual machines placement in a cloud environment by multi-objective programming approaches

Dynamic virtual machines placement in a cloud environment by...

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ICIIBMS 2015 Int C Intelligent Inform BioMedical

作者： Kao, Han-Ying Yang, Yu-Min Huang, Chia-Hui Natl Dong Hwa Univ Dept Comp Sci & Informat Engn Hualien Taiwan Natl Taipei Univ Business Dept Business Adm Taipei Taiwan

ISBN: (纸本)9781479985623

Recently, cloud services and cloud computing have revolutionized both academic research and industrial practices. A corresponding focus on how to improve the performance of cloud computing is growing apace. It is a significant approach to allocate virtual machines (VMs) on a set of physical machines. Computing resources can be utilized effectively with the optimal distribution of the virtual machines among the physical machines. This study aims to establish the dynamic placement model of VMs by multi-objective programming for (1) minimizing energy consumption, (2) maximizing effectiveness of physical machine, and (3) minimizing the task waiting time. Experiments are implemented to verify the effectiveness of the proposed methods.

关键词： cloud computing multi-objective programming dynamic genetic algorithm virtual machine placement

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