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Using a compromise programming framework to integrating spatially specific preference information for forest management problems

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JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 2015年第1-2期22卷 3-15页

作者： Eyvindson, Kyle Kangas, Annika Univ Helsinki Dept Forest Sci POB 27Latokartanonkaari 7 FL-00014 Helsinki Finland

The development of forest management plans is a multi-criteria problem that usually involves multiple stakeholders. In forested recreational areas or natural parks, stakeholders could include government officials, forest companies and visitors to the area. With the progress of mobile phone technology, preference information (including aesthetic values) can be conveniently obtained from stakeholders while they are in the forest. This paper develops a methodological approach that incorporates place-specific opinion preference into the development of alternative forest management plans. Through the use of a modified compromise programming approach, prospective alternatives are developed, which optimize the opinions of stakeholders and the quantity of timber over time depending on specified parameters. The analysis is based on a small simulated forest holding and place-specific simulated opinion data. To allow for a comparison between potential stakeholder groups, the opinion data was generated by a method that produced three separate groups. The results indicate the practical use of place-specific preferences and provide a means to incorporate the information to generate possible alternative plans. In addition, the analysis highlights that by segregating the preference information into groups, the planning of more specific courses of actions can be made. Copyright (C) 2015 John Wiley & Sons, Ltd.

关键词： compromise programming forest management place-specific values

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Airline new route selection using compromise programming - The case of Taiwan-Europe

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2019年 76卷 10-20页

作者： Chang, Yu-Chun Lee, Wei-Hao Wu, Chi-Hung Natl Taiwan Ocean Univ Dept Transportat Sci 2 Pei Ning Rd Keelung 20224 Taiwan

The decision to launch a new route has a huge effect on the outcomes of airlines in the market. In order to find potential destinations for airlines, this paper utilizes a compromise programming method for selecting direct flight routes. The selection framework comprises two objective functions, with one maximizing total revenue and the other minimizing total cost. A case studying Taiwan-European region destinations is interpreted in the analysis. The results indicate that four potential routes, including Madrid, Milan, Munich and Zurich should be added to the airlines' service destinations. Therefore, this research suggested that the airport authority could apply incentives scheme to attract carriers to open new routes and add flight frequencies to strengthen its competitiveness.

关键词： New route Airport Airline compromise programming

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An adaptive compromise programming method for multi-objective path optimization

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JOURNAL OF GEOGRAPHICAL SYSTEMS 2013年第2期15卷 211-228页

作者： Li, Rongrong Leung, Yee Lin, Hui Huang, Bo Chinese Univ Hong Kong Inst Space & Earth Informat Sci Shatin Hong Kong Peoples R China Chinese Univ Hong Kong Inst Environm Energy & Sustainabil Dept Geog & Resource Management Shatin Hong Kong Peoples R China Chinese Univ Hong Kong Inst Space & Earth Informat Sci Dept Geog & Resource Management Shatin Hong Kong Peoples R China

Network routing problems generally involve multiple objectives which may conflict one another. An effective way to solve such problems is to generate a set of Pareto-optimal solutions that is small enough to be handled by a decision maker and large enough to give an overview of all possible trade-offs among the conflicting objectives. To accomplish this, the present paper proposes an adaptive method based on compromise programming to assist decision makers in identifying Pareto-optimal paths, particularly for non-convex problems. This method can provide an unbiased approximation of the Pareto-optimal alternatives by adaptively changing the origin and direction of search in the objective space via the dynamic updating of the largest unexplored region till an appropriately structured Pareto front is captured. To demonstrate the efficacy of the proposed methodology, a case study is carried out for the transportation of dangerous goods in the road network of Hong Kong with the support of geographic information system. The experimental results confirm the effectiveness of the approach.

关键词： Multi-objective optimization compromise programming Multi-objective shortest path Pareto-optimality

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Evaluating Fund Performance by compromise programming with Linear-Quadratic Composite Metric: An Actual Case on The CaixaBank in Spain

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JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 2012年第5-6期19卷 247-255页

作者： Bravo, Mila Ballestero, Enrique Pla-Santamaria, David Univ Politecn Valencia Alcoy Spain

This paper proposes an additive measure on the basis of compromise programming to evaluate fund performance from multiple criteria, of which the most usual are profitability and risk. This proposal is motivated by the fact that compromise programming is a sound decision support model to obtain scores of alternatives by minimizing weighted distances to an ideal point, the weights reflecting the investor's preferences for the criteria. To define the distance objective function, the linear-quadratic composite metric is used, which combines advantages of linear and non-linear objective functions. A critical advantage of compromise programming for fund performance evaluation is that the model can be extended to more than two financial criteria while other measures currently used (either ratio-based or leverage-based measures) only consider two criteria, say, profitability and risk. In the application, three investor's profiles are defined, which involve different weighting systems and lead to different fund rankings. These rankings are compared with domination relationships, the latter formulating if a fund is dominated or non-dominated by convex combinations of other funds. Numerical tables are provided with data, computational process and results, which are analysed. Copyright (C) 2012 John Wiley & Sons, Ltd.

关键词： fund performance compromise programming additive measures ranking domination

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Taguchi Method or compromise programming as Robust Design Optimization Tool: The Case of a Flexible Manufacturing System 12

Taguchi Method or Compromise Programming as Robust Design Op...

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12th International Conference on Informatics in Control Automation and Robotics (ICINCO)

作者： Tshibangu, Wa-Muzemba Anselm Morgan State Univ Dept Ind & Syst Engn 1701 E Cold Spring Lane Baltimore MD 21251 USA

ISBN: (纸本)9789897581496

Competitive advantage of a firm is usually reflected through its superiority in production resources and performance outcomes. In order to achieve high performance (e.g., productivity) and significantly improve product quality, major US industries have promoted and implemented Robust Design (RD) techniques during the last decade. RD is a cost-effective procedure for determining the optimal settings of the control factors that make the product performance insensitive to the influence of noise factors. In this research, we employ and compare two RD optimum-seeking methods to optimize a flexible manufacturing system (FMS). Taguchi Method (TM), which uses robust design concept, i.e., Signal-To-Noise Ratio (S/N) to reduce the output variation, is applied first. Taguchi's approach to robust design drawn much criticism because it relies on the signal-to-noise (S/N) ratio for the optimization procedure. Because of this paramount criticism, a second method known as the compromise programming (CP) approach, i.e., the weighted Tchebycheff, is also used. This method formulates the robust design as a bi-objective robust design (BORD) problem by taking into account the two aspects of the RD problem, i.e. minimize the variation and optimize the mean. This approach seeks to determine the RD solution which is guaranteed to belong to the set of efficient solutions (Pareto points). Both methods use a RD formulation to determine an optimal and robust configuration of the system under study. The results gained through simulations and analytical formulations show that the current ways of handling the multiple aspects of the RD problem by using Taguchi's S/N ratio may not be adequate.

关键词： Robust Design Optimization Taguchi Method compromise programming Fms Simulation

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A multicriteria approach based on Analytic Hierarchy Process and compromise programming in portfolio selection

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JOURNAL OF MULTI-CRITERIA DECISION ANALYSIS 2020年第1-2期27卷 141-146页

作者： Santamaria, Rafael Aguaron, Juan Maria Moreno-Jimenez, Jose Univ Publ Navarra Dept Gest Empresas Pamplona Spain Univ Zaragoza Fac Econ & Empresa GDMZ Gran Via 2 Zaragoza 50005 Spain

The traditional approach to the portfolio selection problem, the mean-variance model, shows limitations because it assumes that any investment opportunity could be meaningfully measured in terms of means and variances of returns. The model should include other criteria, based on liquidity, the characteristics of return distributions, or environmental factors. To incorporate in the model these additional relevant aspects of the problem, alternative methodologies are needed. This paper deals with the problem by using a multicriteria approach based on compromise programming and various options to incorporate the prior information (the norm and the criteria weights). A simplified version of the model has been applied to the stocks included in the Madrid Stock Market IBEX35 index. This article is dedicated to the memory of our colleague and friend Professor Rafael Santamaria, one of the most brilliant Spanish Professors of Finance, who passed away on June 18, 2018, at the age of 57.

关键词： Analytic Hierarchy Process compromise programming portfolio selection

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A Multi-objective Hospital Operating Room Planning and Scheduling Problem Using compromise programming 15th

A Multi-objective Hospital Operating Room Planning and Sched...

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15th Mexican International Conference on Artificial Intelligence (MICAI)

作者： Duenas, Alejandra Di Martinelly, Christine Tutuncu, G. Yazgi Aguado, Joaquin LEM CNRS IESEG Sch Management 3 Rue Digue F-59000 Lille France Izmir Univ Econ Dept Math Sakarya Cad 156 Balcova Izmir Turkey Univ Bamberg Bamberg Germany

ISBN: (纸本)9783319624341;9783319624334

This paper proposes a hybrid compromise programming local search approach with two main characteristics: a capacity to generate non-dominated solutions and the ability to interact with the decision maker. compromise programming is an approach where it is not necessary to determine the entire set of Pareto-optimal solutions but only some of them. These solutions are called compromise solutions and represent a good tradeoff between conflicting objectives. Another advantage of this type of method is that it allows the inclusion of the decision maker's preferences through the definition of weights included in the different metrics used by the method. This approach is tested on an operating room planning process. This process incorporates the operating rooms and the nurse planning simultaneously. Three different objectives were considered: to minimize operating room costs, to minimize the maximum number of nurses needed to participate in surgeries and to minimize the number of open operating rooms. The results show that it is a powerful decision tool that enables the decision makers to apply compromise alongside optimal solutions during an operating room planning process.

关键词： Multi-objective optimization compromise programming Mixed integer programming Local search Operating room scheduling

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Multi-objective route planning for dangerous goods using compromise programming

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JOURNAL OF GEOGRAPHICAL SYSTEMS 2011年第3期13卷 249-271页

作者： Li, Rongrong Leung, Yee Chinese Univ Hong Kong Dept Geog & Resource Management Shatin Hong Kong Peoples R China

The transportation of dangerous goods (DG) can significantly affect the human and natural environment if accidents occur during the transportation process. Hong Kong is a large city with high population density and narrow streets. Due to the land constraints, vehicles carrying DG inevitably have to pass through densely populated areas or their vicinities. Therefore, safe DG transportation is of paramount importance. There is thus an urgent need to review and improve the way trucks carrying DG are being routed on the road networks. Routing of such vehicles should consider not only the operating cost, but also the safety of travelers in the network, the population potentially exposed, and the possible damage inflicted to the surrounding properties and facilities in the event of a DG incident. This research develops a novel methodology for the determination of optimal routes for DG transportation under conflicting objectives by means of the compromise programming approach. With the support of geographical information system (GIS), a case study is carried out for the transportation of DG in the road network of Hong Kong. The experimental results confirm the effectiveness of the proposed approach.

关键词： compromise programming Dangerous goods GIS Multi-objective route planning

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Multi-objective two-stage stochastic unit commitment model for wind-integrated power systems: A compromise programming approach

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2023年第1期152卷

作者： Mena, R. Godoy, M. Catalan, C. Viveros, P. Zio, E. Univ Tecn Federico Santa Maria Dept Ind Engn Santiago Chile MINES Paris PSL CRC Sophia Antipolis France Politecn Milan Energy Dept Milan Italy

In this paper, we introduce a compromise programming (CP) framework for solving a multi-objective two-stage stochastic unit commitment problem characterized by high penetration of wind power. The proposed framework aims at finding best-compromise Pareto efficient on/off schedules, accounting for wind and power demand uncertainties: such solutions must trade off the three objectives of operating cost, CO2 emissions, and wind power curtailment in accordance to the decision maker preferences. To achieve this, we introduce a practical procedure to compute the ideal and Nadir points associated to the multi-objective two-stage stochastic unit commitment problem and propose a linearized l(1) norm-based compromise program to design best-compromise on/off schedules that correspondingly minimize and maximize their weighted distances to the ideal point and to the Nadir point, considering the preference weights assigned by the decision maker to each of the three objective functions. The proposed CP framework is applied to a case study related to the New England IEEE-39 bus test system. The results show that, compared to the schedule obtained through the traditional minimization of operating cost, the designed best-compromised schedules considerably improve CO2 emissions reduction and wind power curtailment performance by conservatively sacrificing operating cost performance.

关键词： Power systems Wind energy Unit commitment Multi-objective optimization Stochastic programming compromise programming

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Assessing temporal complementarity between three variable energy sources through correlation and compromise programming

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ENERGY 2020年 192卷 116637-000页

作者： Canales, Fausto A. Jurasz, Jakub Beluco, Alexandre Kies, Alexander Univ Costa Dept Civil & Environm Calle 58 55-66 Barranquilla 080002 Atlantico Colombia MDH Univ Sch Business Soc & Engn Hogskoleplan 1 S-72220 Vasteras Sweden AGH Univ Sci & Technol Fac Management Dept Engn Management 30 Mickiewicza Ave PL-30059 Krakow Poland Univ Fed Rio Grande do Sul Inst Pesquisas Hidraul Av Bento Goncalves 9500Caixa Postal 15029 BR-91570901 Porto Alegre RS Brazil Goethe Univ Frankfurt Frankfurt Inst Adv Studies Ruth Moufang Str 1 D-60438 Frankfurt Germany

Renewable energies are deployed worldwide to mitigate climate change and push power systems towards sustainability. Nevertheless, the weather-dependent nature and variability of renewable energy sources often hinders their integration to national grids. The combination of different sources to profit from their beneficial complementarity has often been proposed as a partial solution to overcome these issues. This paper introduces a novel method for quantifying total temporal energetic complementarity between three different variable renewable sources, based on well-known mathematical techniques: correlation coefficients and compromise programming. It has the major advantage of allowing the simultaneous assessment of partial and total complementarity, as well as allowing for a linear assessment of complementarity. The method is employed to study the complementarity of wind, solar and hydropower generation on different temporal scales in a region of Poland. Results show that timescale selection has a determinant impact on the estimated value of the total temporal complementarity index. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Energetic complementarity Renewable energy Hybrid power systems Variable renewables compromise programming Correlation

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