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Single-period location models for subsidized housing: Tenant-based subsidies

ANNALS OF OPERATIONS RESEARCH 2003年第1-4期123卷 105-124页

作者： Johnson, MP Univ Pittsburgh H John Heinz III Sch Publ Policy & Management Pittsburgh PA 15213 USA

Previous research has established a need for operations research models to help urban public housing authorities (PHAs) in the U.S. better manage the transition from the traditional model of high-rise public housing developments to tenant-based housing subsidies for market-rate rental units and project-based housing subsidies for scattered-site, low-density public housing. This paper presents the tenant-based subsidized housing location model (TSHLP) that is simplified and applied to a larger and more representative data set than has been done previously. Base-case and sensitivity analyses indicate that model solutions, which are approximations to a Pareto frontier of nondominated potential family allocations, give planners considerable flexibility in choosing alternative housing configurations that can satisfy the needs of various interest groups.

关键词： public sector equity subsidized housing facility location public goods integer programming nonlinear programming multi-objective programming

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A mix integer programming model and solution approach to determine the optimum machine number in the unrelated parallel machine scheduling problem

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1期37卷 329-345页

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

It is assumed that all machines will be used in studies dealing with parallel machine scheduling problems. However, for some businesses having special processes, where large furnaces with very intense energy consumption are used during commissioning, it can be very critical to complete jobs using the least number of furnaces. In addition, for many businesses, doing their jobs with fewer machines creates opportunities for unused machines to be rented to another company or to accept additional jobs as much as the capacity of idle machines. For this reason, in this study, the assumption that all machines will be used has been removed and a mathematical model has been proposed that will decide both which machines will be used and which jobs will be produced in which order on these machines, for the unrelated parallel machine scheduling problem with sequence and machine dependent setup times and machine eligibility restriction. The objectives of the considered problem are minimizing the number of machines to be used and the completion time of the last job. The objective functions of the proposed multi-objective mathematical model are scalarized using the weighted sum method. In order to show the solution performance of the mathematical model, randomly generated test problems were solved with GAMS / CPLEX. To solve the large problems, a local search algorithm and a genetic algorithm have been proposed due to the lack of feasible solutions with GAMS / CPLEX. In the large-scale problem, when all weight pairs are taken into account, genetic algorithm is more successful than local search algorithm an average of 25.64% in terms of solution quality and 50.31% in terms of time.

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A compromise programming approach for cross efficiency measurement in basic two-stage network system

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartA期252卷

作者： Hazhir, Maryam Masoumi Foroughi, Ali Asghar Univ Qom Dept Math Qom Iran

Data envelopment analysis (DEA) is a technique that allows each decision-making unit (DMU) to calculate efficiency using the most favorable weights for inputs and outputs. The resulting efficiency scores are incomparable and difficult to discriminate. Cross-efficiency is a concept for solving the problem of incomparability among the efficiencies of a set of DMUs that are calculated from different weights and is helpful for ranking. In basic DEA, several cross-efficiency evaluation methods with various secondary purposes have been presented, however, the internal mechanism of the DMUs in cross-efficiency evaluation is often neglected. In this study, we use the composition approach for a basic two-stage structure, so that the efficiencies of the divisions are estimated first, and then the overall efficiency of the system is obtained. To solve the linear bi-objective model in the combination approach, we consider a compromise programming problem to find the solution that is as close as possible to the ideal point. Finally, a secondary objective model is proposed to select a weight among the optimal weights of the compromise model, which also guarantees the efficiency of the optimal weight for the bi-objective problem. We use the optimal solution obtained from this model to evaluate cross-efficiency and rank DMUs for a series two-stage system. The proposed approach enables us to rank the DMUs by assessing the performance of each DMU and each of its separate divisions. The validity of the suggested network cross-efficiency evaluation is demonstrated by a numerical example from the literature.

关键词： Network DEA Cross-efficiency evaluation Composition approach multi-objective programming Compromise programming Two-stage system

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A note on solving multi-objective integer indefinite quadratic fractional programs

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ANNALS OF OPERATIONS RESEARCH 2020年第2期289卷 459-462页

作者： Kushwah, Prerna Sharma, Vikas Thapar Inst Engn & Technol Sch Math Patiala Punjab India

In this note we have discussed that a simplex like algorithm to solve a indefinite quadratic fractional programming problem proposed by Mekhilef et al. (Ann Oper Res, 2019. https://***/10.1007/s10479-019-03178-2) fails to find its optimal solution and so it may not generate the actual set of efficient points of the corresponding multi-objective integer indefinite quadratic fractional programs. A counter example in support of this argument is also given.

关键词： multi-objective programming Integer programming Linear programming Quadratic programming Fractional programming Efficient cut Branch and cut

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multi-objective portfolio selection model with fuzzy random returns and a compromise approach-based genetic algorithm

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INFORMATION SCIENCES 2013年 220卷 507-521页

作者： Li, Jun Xu, Jiuping Univ Elect Sci & Technol China Sch Management & Econ Chengdu 610054 Peoples R China Sichuan Univ Uncertainty Decis Making Lab Chengdu 610064 Peoples R China

This paper addresses the multi-objective portfolio selection model with fuzzy random returns for investors by studying three criteria: return, risk and liquidity. In addition, securities historical data, experts' opinions and judgements and investors' different attitudes are considered in the portfolio selection process, such that the investor's individual preference is reflected by an optimistic-pessimistic parameter lambda. To avoid the difficulty of evaluating a large set of efficient solutions and to ensure the selection of the best solution, a compromise approach-based genetic algorithm has been designed to solve the proposed model. In addition, a numerical example is presented to illustrate the proposed algorithm. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Portfolio selection multi-objective programming Fuzzy random variable Compromise solution Genetic algorithms

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multi-choice conic goal programming model-based network data envelopment analysis

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RAIRO-OPERATIONS RESEARCH 2024年第4期58卷 3391-3416页

作者： Deliktas, Derya Ustun, Ozden Demirtas, Ezgi Aktar Arapoglu, Rifat Aykut Kutahya Dumlupinar Univ Fac Engn Dept Ind Engn Kutahya Turkiye Aksaray Univ Fac Engn Dept Ind Engn Aksaray Turkiye Eskisehir Osmangazi Univ Fac Engn Dept Ind Engn Eskisehir Turkiye

In multi-stage processes, classical Data Envelopment Analysis (DEA) acts like a black box and measures the efficiency of decision-making units (DMUs) without considering the internal structure of the system. Unlike classical DEA, recent studies have shown that the overall system efficiency scores are more meaningful if researched using the Network DEA (NDEA) methodology. NDEA performs simultaneous efficiency evaluations of sub-processes and the entire system. Recently, the composition method integrated with multi-objective programming (MOP) has been preferred by many authors to alleviate the drawbacks of earlier methods such as decomposition, slack-based measure (SBM) and the system-centric approach. This study proposes a novel approach incorporating multi-Choice Conic Goal programming into the NDEA (MCCGP-NDEA). It provides a more accurate representation of the Pareto front by revealing potential Pareto optimal solutions which are overlooked by the composition methods. Due to its ability to modify stage weights based on the decision makers' (DMs) preferences, it is likely to gather more samples from the Pareto surface. Computational results on available benchmark problems confirm that the proposed MCCGP-NDEA is a viable alternative to existing methods.

关键词： Data envelopment analysis network DEA multi-choice conic goal programming multi-objective programming

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Optimization of a quadratic programming problem over an integer efficient set

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2024年 441卷

作者： Prerna Sharma, Vikas TIET Sch Math Patiala Punjab India

multi-objective programming problem often contains numerous efficient solutions, which con-fuses the decision-maker. To assist in selecting the most desirable solution, optimizing a function over the efficient set becomes crucial. In this paper, we present a novel method for optimizing a general quadratic function over the efficient set of a multi-objective integer linear programming problem. To solve this problem, a ranking approach and efficiency test is utilized. The proposed methodology obtains a globally optimal solution by systematically scanning ranked solutions of an integer quadratic programming problem until the efficiency condition is satisfied. For generating ranked solutions, we construct a related integer linear programming problem. Then, ranked solutions of the integer linear programming problem are used for enumerating ranked solutions of the integer quadratic programming problem. The convergence of our algorithm is established theoretically, and its steps are illustrated using a numerical example. Aparticular case of the proposed method for optimizing a linear function over the efficient set of a multi-objective integer linear programming problem is also discussed. Further, extensive computational results demonstrate the effectiveness of our method for solving problems with large number of constraints, variables, and objective functions. Moreover, comparative analysis shows that the developed algorithm came out to be computationally more efficient as compared to the existing state-of-the-art algorithms.

关键词： Efficient set multi-objective programming Quadratic programming Integer programming

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multi-objective and Stochastic Optimization Model of Transit Containers Storage in a Transshipment port yard

Multi-objective and Stochastic Optimization Model of Transit...

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2nd International Conference on Information Technology and Management Innovation (ICITMI 2013)

作者： Wang, Bin Yang, Tao Shanghai Second Polytech Univ Sch Econ & Management Shanghai Peoples R China

ISBN: (纸本)9783037858646

The load/unload task in a transshipment port yard is more heavy and the time requirmement is more tight than an export port. A multi-objective and stochastic programming optimization model for containers stacking in the storage yard of a transshipment port is built to improve its efficiency. The objective function is to minimize the number of yard cranes used in the storage yard and balance the workload among different blocks during the planning period. The decision variables include the number of transit containers assigned to yard-bits, yard cranes distributed to blocks, yard-bits with high and low workload in a block. The constraints include meeting the shipping requirement, storage capacity and operational capacity of yard cranes. The numbers of transit containers are stochastic. The model is tranfered into an integer programming and solved by Lingo9.0. The simulation is done to recover the relation between workload level and the number of yard crane used and the workload balance. The model can be used to yard stacking management and lift its level for a transshipment port.

关键词： Storage yard Containers Yard crane multi-objective programming Stochastic programming

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multi-objective analysis of school district regionalization alternatives in Connecticut

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PROFESSIONAL GEOGRAPHER 1996年第1期48卷 1-14页

作者： November, SM Cromley, RG Cromley, EK UNIV CONNECTICUT DEPT GEOGSTORRSCT 06269 USA

This paper demonstrates the utility of multi-objective programming techniques as an aid in educational planning and the limitations to the achievement of any educational objective given the spatial distribution of existing disparities. A case study of Connecticut is used to examine alternative scenarios for the implementation of interdistrict responses to a number of issues facing the state's public education system. A mixed-integer, goal programming model is formulated where the goal constraints are to minimize disparities in: (1) minority enrollments, (2) grand-list/student ratios, (3) student-teacher ratios, and (4) overall enrollment. Results show that the traditional distance-minimizing or transportation-minimizing objectives are in conflict with all other aims of equity and quality of educational opportunities. The geographic distribution of minority students and grand-list property values also limited the reduction of statewide disparities in these goals.

关键词： school districting location-allocation modeling multi-objective programming

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Mine Ore Blending planning and management Based on the Fuzzy multi-objective Optimization Algorithm

Mine Ore Blending planning and management Based on the Fuzzy...

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International Seminar on Business and Information Management (ISBIM 2008)

作者： Xu, T. J. Yang, P. Liu, Z. Q. Minist Educ Key Lab High Efficient Min Metall Ore Deposit Beijing 100083 Peoples R China Jinchengxin Min Construct Grp Co Ltd Beijing 100089 Peoples R China

ISBN: (纸本)9780769535609

In a time of digitalization and informationization for Mine enterprise, based on the complication of multiobjective ore blending planning and management, a question of fuzzy multi-objective ore blending is proposed. Then according to linguistic preference information and satisfying degree of decision maker, a fuzzy multi-objective optimization algorithm is designed. The algorithm effectively solves the difficulties in multi-objective decisions, such as difficult to quantify certain objectives and restrictions and to weigh decision objectives subjectively, and different dimensions of objectives. It has also the Characteristics of flexibility and sensitivity, which is verified through a application example of certain mine, it is a practical, great universal method or means for the mine ore blending planning and management.

关键词： multi-objective programming ore blending model fuzzy optimization algorithm satisfying degree ore blending

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