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A bi-level multi-objective linear fractional programming for water consumption structure optimization based on water shortage risk

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JOURNAL OF CLEANER PRODUCTION 2019年 237卷 117829-000页

作者： Wang, Youzhi Liu, Liu Guo, Shanshan Yue, Qiong Guo, Ping China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China

In this study, a framework of a bi-level multi-objective linear fractional programming (BMLFP) approach is developed for the optimization of water consumption structure based on water shortage risk. It incorporates linear fractional programming (LFP), multi-objective programming (MOP) into bi-level programming (BP). The model considers the water shortage risk measured by interior-outer-set risk assessment method, and integrates it into inexact water resources optimization model. The complicated model not only can enhance the conventional programming method through the interactive influence and mutual restriction between the upper- and lower-level decision processes, and multiple objectives, but also improve the robustness of conventional programming methods by integrating the water shortage risk. Besides, the model could achieve the tradeoff between equality and economic benefit of system and figure out the interaction amid water shortage risk, water allocation and objectives. It is applied to a case study to conduct water resources management among different water users including agricultural, industrial, domestic, and ecological sectors in the middle reaches of Heihe River Basin, northwest China. The water allocation schemes with ten water-shortage risk scenarios is formed to compare the influence of water shortage degree on water allocation and figure out the optimal water allocation schemes. Besides, the performance of the developed model is enhanced by comparing with the two-level linear fractional water management (TLFWM) model and actual condition. The results indicate that the water shortage belongs to general risk area, and the water-shortage risk has obvious effect on agricultural water allocations while has insensitive influence on that of the industrial, domestic and ecological sectors. Compared with the TLFWM model and actual condition, the developed BMLFP model could improve the equality and benefit of system and lessen the water allocation. The decisi

关键词： Water shortage risk Bi-level programming Linear fractional programming multi-objective programming Equality Efficiency

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Optimisation of multi-level logistics network for agricultural products under community group buying model

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS 2023年第1期10卷

作者： Li, Chenxing Shi, Xianliang Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China

This paper introduces a rapidly developing new online retail model, community group buying, and proposes a three-level agricultural logistics network optimisation model. Under the community group buysing model, it is necessary to use different types of vehicles for transportation of agricultural products with different temperature control requirements. The study establishes a multi-objective mixed integer programming model with the objectives of shortest transportation time and minimum total cost, taking into account the freshness penalty cost incurred during transport. The multi-objective problem is transformed into a single objective by normalisation and weighting methods. According to the calculation for the actual case, this paper solves the problems of community group buying grid warehouse location, multiple vehicles use strategy, loading capacity, transportation path optimisation and self-pickup station demand allocation. In addition, through sensitivity analysis, the management insights of community group buying enterprises are obtained: (1) The community group buying enterprises should use brokers of the community group buying model to enhance customer stickiness;(2) The enterprises should focus on developing business in less developed regions;(3) The enterprises need to adjust the proportion of time efficiency and logistics costs according to the real situation.

关键词： Community group buying agricultural logistics network multi-objective programming multi-commodity and multi-vehicle freshness penalty

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Hierarchical Resource Allocation: Balancing Throughput and Energy Efficiency in Wireless Systems

Hierarchical Resource Allocation: Balancing Throughput and E...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Matthiesen, Bho Jorswieck, Eduard A. Popovski, Petar Univ Bremen Dept Commun Engn Bremen Germany TU Braunschweig Dept Informat Theory & Commun Syst Braunschweig Germany Aalborg Univ Dept Elect Syst Aalborg Denmark

ISBN: (纸本)9781728195070

A main challenge of 5G and beyond wireless systems is to efficiently utilize the available spectrum and simultaneously reduce the energy consumption. From the radio resource allocation perspective, the solution to this problem is to maximize the energy efficiency instead of the throughput. This results in the optimal benefit-cost ratio between data rate and energy consumption. It also often leads to a considerable reduction in throughput and, hence, an underutilization of the available spectrum. Contemporary approaches to balance these metrics based on multi-objective programming theory often lack operational meaning and finding the correct operating point requires careful experimentation and calibration. Instead, we propose the novel concept of hierarchical resource allocation where conflicting objectives are ordered by their importance. This results in a resource allocation algorithm that strives to minimize the transmit power while keeping the data rate close the maximum achievable throughput. In a typical multi-cell scenario, this strategy is shown to reduces the transmit power consumption by 65% at the cost of a 5% decrease in throughput. Moreover, this strategy also saves energy in scenarios where global energy efficiency maximization fails to achieve any gain over throughput maximization.

关键词： multi-objective programming global optimization hierarchical optimization mixed monotonic programming

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A bi-objective mathematical model for an unrelated parallel machine scheduling problem with job-splitting

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GA...

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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2022年第4期37卷 2293-2307页

作者： Sarac, Tugba Tutumlu, Busra Eskisehir Osmangazi Univ Fac Engn & Architecture Ind Enginering Dept TR-26480 Eskisehir Turkey Kutahya Dumlupinar Univ Fac Engn Ind Enginering Deparment TR-43100 Kutahya Turkey

Studies dealing with parallel machine scheduling problems generally assume that jobs are not split. However, splitting of jobs can offer opportunities such as delivering the jobs on time or evenly distributing the jobs to the machines. In this study, two different multi-objective mathematical models are proposed for the unrelated parallel machine scheduling problem without and with job-splitting. The first model is for the unrelated parallel machine scheduling problem without job-splitting and it was developed based on the model proposed by Sarac and Tutumlu [1]. In the second model, in which the jobs can split, besides the machines to which the jobs will be assigned and their order, it is also determined how the jobs will split and in which ratios the jobs will be processed on which machines. The objectives of both models are to minimize the completion time of the last job and the number of machines to be used. multi-objective models were transformed into a single-objective structure with the epsilon constraint method. Randomly generated test problems were solved with the proposed models using the GAMS/Cplex solver, and the results were compared. Considering the problems for which the optimum solution is obtained, the first model found a solution in an average of 85% less time than the model in the literature [1], and the second model shortens the completion time of the last job in an average of 14%. In addition, a mathematical heuristic algorithm is proposed for solving large-size problems.

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Bi-Level multi-objective Production Planning Problem with multi-Choice Parameters: A Fuzzy Goal programming Algorithm

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ALGORITHMS 2019年第7期12卷 143-143页

作者： Kamal, Murshid Gupta, Srikant Chatterjee, Prasenjit Pamucar, Dragan Stevic, Zeljko Aligarh Muslim Univ Dept Stat & Operat Res Aligarh 202002 Uttar Pradesh India Jaipuria Inst Management Jaipur 302022 Rajasthan India MCKV Inst Engn Dept Mech Engn Howrah 711204 W Bengal India Univ Def Mil Acad Dept Logist Belgrade 11000 Serbia Univ East Sarajevo Fac Transport & Traff Engn Doboj Doboj 71000 Bosnia & Herceg

This paper deals with the modeling and optimization of a bi-level multi-objective production planning problem, where some of the coefficients of objective functions and parameters of constraints are multi-choice. A general transformation technique based on a binary variable has been used to transform the multi-choices parameters of the problem into their equivalent deterministic form. Finally, two different types of secularization technique have been used to achieve the maximum degree of individually membership goals by minimizing their deviational variables and obtained the most satisfactory solution of the formulated problem. An illustrative real case study of production planning has been discussed and, also compared to validate the efficiency and usefulness of the proposed work.

关键词： production planning bi-level programming multi-objective programming fuzzy goal programming multi-choice parameter

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Improving the AquaCrop model to achieve direct simulation of evapotranspiration under nitrogen stress and joint simulation-optimization of irrigation and fertilizer schedules

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AGRICULTURAL WATER MANAGEMENT 2022年第0期266卷

作者： Wu, Hui Yue, Qiong Guo, Ping Xu, Xiaoyu Huang, Xi China Agr Univ Ctr Agr Water Res China Beijing 100083 Peoples R China Res Stn Efficient Water Use Oasis Agr Wuwei Gansu Natl Field Sci Observat Wuwei 733000 Gansu Peoples R China

Water and fertilizer management strategy profoundly influences crop yield, water and nitrogen use efficiency. In this study, a framework for joint simulation-optimization of irrigation and fertilizer schedules (JSOIFS) was established by coupling the improved AquaCrop model, W*N-Jensen model and multi-objective programming. Firstly, the AquaCrop model was modified to simulate evapotranspiration (ET) under nitrogen stress through introducing the concept of shoot actual, critical and minimal nitrogen concentration. The accuracy and applicability of the improved AquaCrop model to simulate ET were verified, taking seed maize of Shiyanghe River Basin as a case. On the basis, an optimization model with the objective of maximum yield calculated by W*NJensen model and water use efficiency was developed under the scenarios of different levels of available water and nitrogen, and initial soil mineral nitrogen content. Results showed that the improved model can simulate canopy cover (CC) and ET well with and without water stress. Meanwhile, the precision for CC, biomass, ET and yield of seed maize can be guaranteed when water and nitrogen stress coexist. It indicated that the improved model can be used for irrigation and fertilizer management. The optimal irrigation and fertilizer schedules pointed out that the irrigation and nitrogen application, and initial soil mineral nitrogen all have significant effects on yield. In low fertility soils, irrigation should be concentrated during tasseling stage and fertilization is as critical as irrigation. Conversely, in high fertility soils, irrigation should be dispersed throughout the growth period. Water and nitrogen use efficiency have been promoted compared with the status quo. The recommended water and nitrogen application for seed maize are 150-200 mm and 100-150 kg N/ha, respectively, in study area with the mean soil mineral nitrogen of 182 kg N/ha. The improvement of ET simulation performance of AquaCrop model under simultaneou

关键词： Optimization Irrigation and fertilizer management AquaCrop multi-objective programming

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An extended multi-objective mixed integer programming for water resources management through possibility theory

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ECOLOGICAL INFORMATICS 2019年 54卷 100992-000页

作者： Nematian, Javad Movahhed, Sevda Rezazadeh Univ Tabriz Fac Mech Engn Dept Ind Engn POB 51666-14766 Tabriz Iran

In this study, we develop an extended multi-objective mixed integer programming (EMOMIP) approach for water resources management under uncertainty, in which the parameters are fuzzy random variables while the decision variables are interval variables. Furthermore, some alternatives are considered to retrieve the difference between the quantities of promised water-allocation targets and the actual allocated water. Then, the proposed EMOMIP for the problem is solved by a new method using fuzzy random chance-constrained programming based on the idea of possibility theory. This method can satisfy both optimistic and pessimistic decision makers simultaneously. Finally, a real example is given to explain the proposed method.

关键词： Water resources management multi-objective programming Mixed integer programming Possibility theory

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multi-Criteria and multi-Class Traffic User Equilibrium Model under Uncertainties

Multi-Criteria and Multi-Class Traffic User Equilibrium Mode...

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International Conference on Smart Transportation and City Engineering

作者： Li, Ming Jiangsu Prov Planning & Design Grp Co Ltd Nanjing Peoples R China

ISBN: (数字)9781510649767

ISBN: (纸本)9781510649767;9781510649750

Traditional traffic assignment model suffers from its criteria which are travel time only, travel time and distance, travel time and reliability. All of these criteria influence route choice behavior. multi-criteria user equilibrium model considering travel time, travel time reliability and travel distance was proposed. It was proved that the week multi-criteria user equilibrium model is a generalization of user equilibrium (UE) model and travel time budget (TTB) model. multi-criteria and multi-class user equilibrium (MMUE) model was established to overcome the shortcoming of multi solution of multi-criteria user equilibrium model. Quasi-method of successive average (QMSA) was designed to solve the MMUE model. An example was used to test the speed and accuracy of proposed algorithm. And the differences of MMUE, UE and TTB model were compared. Experiments had shown that the QMSA algorithm could be quickly convergent. It is more realistic to consider the different travel value for each traveler in MMUE model.

关键词： traffic engineering user equilibrium model multi-objective programming traffic assignment

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Designing an integrated pharmaceutical relief chain network under demand uncertainty

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2020年 136卷 101867-000页

作者： Akbarpour, Mina Torabi, S. Ali Ghavamifar, Ali Univ Tehran Sch Ind Engn Coll Engn Tehran Iran

This paper addresses an integrated relief network design problem for pharmaceutical items. The proposed bi-objective model accounts for perishability of pharmaceutical items, mobility of relief facilities, and benefits from a cooperative coverage mechanism in designing the network. A min-max robust model is developed to tackle the demand uncertainty. Several numerical experiments are conducted to explore the performance of the robust model. Also, by conducting a real case study, useful managerial insights are derived through performing several sensitivity analyses. The numerical results reveal that using the min-max robust model enhances the pharmaceutical relief network's effectiveness and efficiency considerably.

关键词： Humanitarian logistics Pharmaceutical relief items Perishability multi-objective programming Robust optimization

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Optimization of the sustainable food supply chain with integrative data envelopment analysis approach

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INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2024年第4期19卷 278-293页

作者： Nannar, Siwaporn Sindhuchao, Sombat Chaiyaphan, Chewaphorn Ransikarbum, Kasin Surindra Rajabhat Univ Dept Ind Technol Surin Thailand Ubon Ratchathani Univ Dept Ind Engn Ubon Ratchathani Thailand Thai Nichi Inst Technol Dept Logist & Supply Chain Management Bangkok Thailand

In this study, the supply chain system of the food supply chain (FSC) is assessed. Initially, the operations of farmers are examined using the Data Envelopment Analysis (DEA) technique. Then, locations of relatively efficient farmers are used as potential collection sites for the distribution at the downstream operations. Next, the multi-objective Optimization Model is proposed to examine location and distribution channels under the sustainability paradigm. That is, the economic criterion is primarily considered by focusing on minimizing the total supply cost. The social criterion is next deliberated by evaluating the equality aspect of farmers for the fair proportion of vegetable supply. Then, the environmental criterion is incorporated by assessing the CO2 emissions of food transportation activity. Additionally, a trade-off analysis is analyzed to investigate the conflicting behavior of model using the Non-Preemptive programming method. The sensitivity analysis is further examined by varying the time-requirement parameter to verify the model functionalities. Finally, the regional case study in Thailand based on the food supply data is applied to validate the model. Given that farmers are distant from diverse locations, the results of our study can provide a strategic choice for key decision-makers in the FSC network under sustainability consideration.

关键词： Food supply chain sustainability data envelopment analysis multi-objective programming non-preemptive method

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