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International Conference on Information Technology and Computer Application Engineering (ITCAE)

作者： Miao, Hong Mei Li, Xiang You Yanan Univ Coll Physis & Elect Informat Yanan Shaanxi Peoples R China Yanan Univ Coll Math & Comp Sci Yanan Shaanxi Peoples R China

In this paper, a class of multi-objective programming is considered, in which related functions are B - (p, r, a)-invex functions, mixed dual problem is researched, many duality theorems are proved under weaker convex... 详细信息

ISBN: (纸本)9781315813288;9781138000797

关键词： B - (p, r, a)-invex function multi-objective programming mixed duality

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Bi-level multi-objective programming problem with fuzzy demands: a fuzzy goal programming algorithm

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OPSEARCH 2014年第2期51卷 280-296页

作者： Baky, Ibrahim A. Eid, Mohamed H. El Sayed, Mohamed A. Benha Univ Fac Engn Dept Basic Sci Banha El Qalyoubia Egypt Benha Univ Fac Engn Shoubra Dept Engn Math & Phys Banha El Qalyoubia Egypt

In this paper, a fuzzy goal programming (FGP) algorithm for solving bi-level multi- objective programming problems with fuzzy demands is presented. These fuzzy demands reflect the experts' imprecise or fuzzy understandings of the nature of parameters in the problem formulation process are assumed to be characterized as fuzzy numbers. Using the level sets of fuzzy parameters, the corresponding non fuzzy bilevel programming problem is introduced. In the proposed algorithm, the membership functions for the defined fuzzy goals of all objective functions at the two levels, as well as the membership functions for the vector of decision variables controlled by FLDM are developed in the model formulation of the problem. Then FGP algorithm is used to achieve the highest degree of each of the membership goals by minimizing their deviational variables and thereby obtaining the most satisfactory solution for all decision makers. Illustrative numerical example is given to demonstrate the proposed algorithm.

关键词： Bi-level programming Fuzzy sets Fuzzy demands Goal programming Fuzzy goal programming multi-objective programming

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An interactive dynamic multi-objective programming model to support better land use planning

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LAND USE POLICY 2014年 36卷 13-22页

作者： Chang, Yang-Chi Ko, Tsung-Ting Natl Sun Yat Sen Univ Dept Marine Environm & Engn Kaohsiung 80424 Taiwan Helmholtz Zentrum Geesthacht Inst Coastal Res D-21502 Geesthacht Germany

This study develops a dynamic multi-objective programming (DMOP) approach to handle problems of optimization under conditions of uncertainty typified by multiple goals and dynamic subsystems. The proposed approach seamlessly integrates multi-objective programming, fuzzy set theory, and system dynamics tools to conduct optimal land use planning in dynamic and complex environmental systems. Based on the DMOP approach, this study constructs an interactive dynamic multi-objective programming model, investigates the connection between land use and future urban development, and incorporates the preferences of decision makers using a compromise index. A case study from Taiwan shows that the proposed modeling framework can accommodate more complete information, allowing improvements to be made in strategic planning for land use. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Land use planning multi-objective programming Fuzzy set theory System dynamics

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Water-energy-ecosystem nexus modeling using multi-objective, non-linear programming in a regulated river: Exploring tradeoffs among environmental flows, cascaded small hydropower, and inter-basin water diversion projects

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022年 308卷 114582-114582页

作者： Yin, Dongqin Li, Xiang Wang, Fang Liu, Yang Croke, Barry F. W. J. Jakeman, Anthony China Agr Univ Coll Land Sci & Technol Beijing Peoples R China China Inst Water Resources & Hydropower Res State Key Lab Simulat & Regulat Water Cycle River Beijing Peoples R China Minist Water Resources Key Lab Sediment Sci & Northern River Regulat Beijing Peoples R China Qinghai Univ State Key Lab Plateau Ecol & Agr Xining Peoples R China Australian Natl Univ Fenner Sch Environm & Soc Canberra Australia Australian Natl Univ Math Sci Inst Canberra Australia

Small hydropower (SHP) possesses significant economic, technical, and environmental advantages, and accounts for a large proportion of hydropower development in China. However, the concentrated, cascaded, and diversion-type development of SHP has resulted in long-distance dewatering of river sections, and inter-basin water transfers have led to severe exploitation of water resources and damage to river ecosystems. In this paper, the Datong River Basin, a secondary sub-basin of the Yellow River Basin in China, was selected as the illustrative case, which includes 22 hydropower projects (HPPs) and three inter-basin water diversion projects (WDPs). A nexus system model was established that used weighted multi-objective programming to consider three main objectives: the water resources utilization (local water withdrawal and inter-basin water transfer), energy production (by cascaded HPPs), and riverine environmental conservation. The Tennant method was used to estimate the environmental flows (e-flows) at the cross-sections immediately downstream of the dam/sluice gate and immediately downstream of the hydropower plant of diversion-type HPPs. The decreased percentage of regulated flow in comparison with runoff and the guaranteed rate of e-flow at the control cross-section were introduced to assess the degree of environmental impact to the river. Using a historical series of runoff data during 1956-2016 as the model input (i.e., implicit stochastic method), the multi-start solver of nonlinear programming of LINGO software was used to conduct optimizations and analyses for multiple scenarios (with/ without e-flow, with consideration of various levels of e-flow, and with/without water resources utilization). The sectoral linkages relating to the water-energy-ecosystem (WEE) nexus were quantitatively identified. The possible influences of different boundary conditions (i.e., initial/final reservoir storage, inter-basin water diversion capacity, and climate change) on the W

关键词： Reservoir operation Hydropower Inter-basin water diversion Environmental flows multi-objective programming

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Mathematical programming models to assist the evaluation of shipbrokers

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第1期18卷 407-416页

作者： Koronakos, Gregory Smirlis, Yiannis Plitsos, Stathis Univ Piraeus Dept Informat Piraeus Greece Univ Pireaus Sch Econ Business & Int Studies Piraeus Greece Univ Piraeus Dept Ind Management & Technol Piraeus Greece

Shipbrokers play a key role in maritime industry by acting as intermediates between shipping companies and the market. They undertake various chartering, buying or selling operations. In this paper, we propose a mathematical programming approach for the evaluation and selection of shipbrokers. Specifically, the score of each ship broker is a composite measure that is derived by aggregating a set of performance criteria, e.g., reputation, etc. The developed mathematical programming models enable the aggregation and weighting of the criteria. We employ three optimization models to explore the effect of different weighting schemes on the scores and ranking of the shipbrokers. The models that provide a common set of weights for all the shipbrokers establish the appropriate ground for comparisons among them. Also, our models facilitate the incorporation of user priorities over the criteria in the form of weight restrictions. The proposed approach is illustrated by assessing seven shipbroker offers for selling a dry-bulk ship using four criteria, namely revenue, brokerage fee, brokerage time and terms & conditions.

关键词： Shipbrokers maritime industry mathematical programming multi-objective programming

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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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International Conference on Intelligent Informatics and Biomedical Sciences

作者： Han-Ying Kao Yu-Min Yang Chia-Hui Huang Dept. of Computer Science & Information Engineering National Dong Hwa University Dept. of Business Administration National Taipei University of Business

ISBN: (纸本)9781479985630

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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Optimizing vendor selection in food supply chains: a goal programming approach using interval type-2 trapezoidal fuzzy numbers

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2025年第4期16卷 1607-1631页

作者： Gupta, Srikant Gupta, Neha Kamal, Murshid Chatterjee, Prasenjit Jaipuria Inst Management Dept Operat & Decis Sci Jaipur India Amity Univ Uttar Pradesh Amity Sch Business Noida India Aligarh Muslim Univ Dept Stat & Operat Res Aligarh India Vilnius Gediminas Tech Univ Inst Sustainable Construct Lab Smart Bldg Syst LT-10223 Vilnius Lithuania Yuan Ze Univ Coll Engn Taoyuan Taiwan

The selection of an effective and efficient vendor plays a crucial role in achieving a competitive advantage in food supply chain management. This study focuses on the complex decision-making process of vendor selection problem, considering multiple quantitative and qualitative factors. The primary objectives of this research are to minimize net ordering costs, transportation costs, and late deliveries. Recognizing the presence of uncertainty in input parameters, Interval type-2 trapezoidal fuzzy numbers are used to effectively capture and represent this uncertainty. Through the calculation of expected values, a precise equivalent form is derived. The study employed exponential smoothing forecasting analysis to estimate product demand accurately, reducing the risk of shortages and associated financial losses. To attain a mutually satisfactory solution, a fuzzy goal programming methodology was applied. A numerical example was presented to illustrate the methodology's practical applicability and provide deeper insights into its underlying concepts. The solution successfully minimized the net ordering cost for aggregate demand to a value of 6,115,073. The total net cost of transportation for all products was reduced to 279,361, and the number of vendors' late deliveries was minimized to 153,152. The order quantities for the selected vendors were determined as 5236, 9376, 6358, and 4360 units, respectively. Vendors 1, 3, and 4 exhibited superior performance, whereas Vendor 2 experienced a substantial reduction in allocation due to poor performance.

关键词： Vendor selection Fuzzy goal programming multi-objective programming Time series Interval type-2 trapezoidal fuzzy numbers

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Sustainable Management and Environmental Protection for Basin Water Allocation: Differential Game-based multiobjective programming

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WATER RESOURCES MANAGEMENT 2023年第1期37卷 1-20页

作者： Di, Danyang Shi, Qi Wu, Zening Wang, Huiliang Zhengzhou Univ Sch Water Conservancy Engn Zhengzhou Peoples R China

It is important to manage water resources via emergy theory and its implementation mechanism for water dispatching while considering both economic development and environmental needs. The contribution of this paper is to propose a multi-objective dynamic differential game that can determine the optimal tax rate (OTR), optimal trading quantity of water (OTQW) in each province, and optimal bargain price (OBP) to balance resource consumption, economic development and environmental protection. Considering the sustainability of the ecological environment, the quantification of negative sewage value and net carbon emission constraints are introduced into the water allocation. To maximize the target revenue functions, minimize the net carbon emission constraints and obtain sustainable equilibrium solutions in this triple-level game, the costate function, Hamiltonian, and Lagrangian multiplier method are introduced. Then, a water dispatching structure is constructed for error correction between the predicted and actual runoff of the YRB. Taking the Yellow River Basin as an example, the validity of the proposed framework and solution method were verified under different hydrological years, with 6.5% similar to 9.1% higher economic benefits than other schemes and 4.3% similar to 5.9% lower net carbon emissions than other schemes. Compared to previous studies, this scheme can better meet the requirements of sustainable development and environmental protection.

关键词： Sustainability Coordinated development Water allocation multi-objective programming

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Genetic algorithm based fuzzy programming approach for multi-objective linear fractional stochastic transportation problem involving four-parameter Burr distribution

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2020年第1期11卷 93-109页

作者： Abebaw Gessesse, Adane Mishra, Rajashree Acharya, Mitali Madhumita Das, Kedar Nath Deemed be Univ Dept Math KIIT Bhubaneswar 751024 Odisha India Dept Math NIT Silchar Silchar 788010 Assam India

In real life situations, it is difficult to handle multi-objective linear fractional stochastic transportation problem. It can't be solved directly using mathematical programming approaches. In this paper, a solution procedure is proposed for the above problem using a genetic algorithm based fuzzy programming method. The supply and demand parameters of the said problem follow four-parameters Burr distribution. The proposed approach omits the derivation of deterministic equivalent form as required in case of classical approach. In the given methodology, initially the probabilistic constraints present in the problem are tackled using stochastic programming combining the strategy adopted in genetic algorithm. Throughout the problem, feasibility criteria is maintained. Then after, the non-dominated solution are obtained using genetic algorithm based fuzzy programming approach. In the proposed approach, the concept of fuzzy programming approach is inserted in the genetic algorithm cycle. The proposed algorithm has been compared with fuzzy programming approach and implemented on two examples. The result shows the efficacy of the proposed algorithm over fuzzy programming approach.

关键词： multi-objective programming Stochastic programming Fractional transportation problem Fuzzy programming Genetic algorithm

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Fully intuitionistic fuzzy multi-level linear fractional programming problem

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ALEXANDRIA ENGINEERING JOURNAL 2023年 77卷 684-694页

作者： Fathy, E. Ammar, E. Helmy, M. A. Helwan Univ Fac Sci Dept Math Helwan Egypt Tanta Univ Fac Sci Dept Math Tanta Egypt Inst Natl Planning Planning Tech Ctr Nasar City Egypt

In many real situations, it is frequently difficult to accurately determine the membership and non-membership degrees related to an element of the set with complete satisfaction because of the ambiguity in the input data. In instances like these, intuitionistic fuzzy (IF) numbers are crucial. We present a simple approach in this paper to solve the fully intuitionistic fuzzy multi-level linear fractional programming (FIFMLLFP) problem. By applying the new suggested approach to the problem under consideration, each level of the FIFMLLFP problem is converted into five crisp linear (MLMOLFP) problems, where each crisp problem has an additional bounded variables constraint and the upper problems' optimization variables are treated as parameters. This is done by using an iterative technique for linearizing fractional objectives. We converted the MLMOLFP problem into a multilevel multiobjective linear programming (MLMOLP) problem, in addition to the & epsilon;-constraint method that is used to reduce MLMOLP problem to a single objective linear programming problem. The method is demonstrated stepby-step with a numerical example.

关键词： Linear fractional programming multi-level linear programming multi-objective programming Interactive approach Intuitionistic fuzzy numbers

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