检索结果-内蒙古大学图书馆

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第3期264卷 978-993页

作者： Rodriguez-Espindola, Oscar Albores, Pavel Brewster, Christopher Aston Business Sch OIM Grp Birmingham B4 7ET W Midlands England TNO Data Sci Grp NL-3769 DE Soesterberg Netherlands

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence. This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities. The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Humanitarian logistics multiple objective programming OR in disaster relief Disaster preparedness

来源：评论

学校读者我要写书评

暂无评论

A novel approach for exploring the trade-offs between several features of students' well-being

引用

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2022年第3期29卷 1723-1748页

作者： Gonzalez-Gallardo, S. Henriques, C. O. Marcenaro-Gutierrez, O. D. Luque, M. Univ Malaga Dept Appl Econ Math C Ejido 6 Malaga 29071 Spain Polytech Inst Coimbra ISCAC Business Sch Quinta Agr P-3040316 Coimbra Portugal Univ Coimbra INESC Coimbra DEEC Polo 2 P-3030290 Coimbra Portugal Univ Malaga Dept Appl Econ Stat & Econometr C Ejido 6 Malaga 29071 Spain

We propose a novel approach to explore the trade-offs between four features of students' well-being (anxiety, motivation, sense of belonging, and bullying). On the one hand, a multiobjective interval problem is formulated by considering these distinct components of well-being as objective functions, being then instantiated with confidence intervals obtained from distinct econometric estimations. Then, the problem is solved through the use of a reference point approach that allows accounting for the decision maker's preferences by considering a set of weight vectors that can be used to express his/her preferences regarding the importance that should be given to each objective function. The results provide information on how the improvement of one objective might affect the remaining objectives. Furthermore, the student's profile corresponding to each scrutinized solution is also made available. Overall, the results claim that bullying is the most affected objective, highlighting the need to foster antibullying education policies in Spanish schools, according to PISA 2015 data. Finally, some educational polices are suggested in order to enhance students' well-being.

关键词： econometric analysis interval programming multiple objective programming students’ well‐ being

来源：评论

学校读者我要写书评

暂无评论

Solving biobjective combinatorial max-ordering problems by ranking methods and a two-phases approach

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2003年第3期147卷 657-664页

作者： Ehrgott, M Skriver, AJV Univ Auckland Dept Engn Sci Auckland New Zealand Aarhus Univ Dept Operat Res DK-8000 Aarhus C Denmark

In this paper we propose a new method to solve biobjective combinatorial optimization problems of the max-ordering type. The method is based on the two-phases method and ranking algorithms to efficiently construct K-best solutions for the underlying (single objective) combinatorial problem. We show that the method overcomes some of the difficulties of procedures proposed earlier. We illustrate this by an example and discuss the difficulties in extending it to more than two objectives. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： multiple objective programming max-ordering problems ranking methods combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

GP-DEMO: Differential Evolution for Multiobjective Optimization based on Gaussian Process models

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第2期243卷 347-361页

作者： Mlakar, Miha Petelin, Dejan Tusar, Tea Filipic, Bogdan Jozef Stefan Inst SI-1000 Ljubljana Slovenia Jozef Stefan Int Postgrad Sch SI-1000 Ljubljana Slovenia

This paper proposes a novel surrogate-model-based multiobjective evolutionary algorithm called Differential Evolution for Multiobjective Optimization based on Gaussian Process models (GP-DEMO). The algorithm is based on the newly defined relations for comparing solutions under uncertainty. These relations minimize the possibility of wrongly performed comparisons of solutions due to inaccurate surrogate model approximations. The GP-DEMO algorithm was tested on several benchmark problems and two computationally expensive real-world problems. To be able to assess the results we compared them with another surrogate-model-based algorithm called Generational Evolution Control (GEC) and with the Differential Evolution for Multiobjective Optimization (DEMO). The quality of the results obtained with GP-DEMO was similar to the results obtained with DEMO, but with significantly fewer exactly evaluated solutions during the optimization process. The quality of the results obtained with GEC was lower compared to the quality gained with GP-DEMO and DEMO, mainly due to wrongly performed comparisons of the inaccurately approximated solutions. (C) 2014 Elsevier B.V. All rights reserved.

关键词： multiple objective programming Evolutionary algorithms Surrogate models Gaussian Process modeling Probable Pareto dominance

来源：评论

学校读者我要写书评

暂无评论

A multivariate robust parameter optimization approach based on Principal Component Analysis with combined arrays

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2014年第1期74卷 186-198页

作者： de Paiva, Anderson Paulo Gomes, Jose Henrique F. Peruchi, Rogerio Santana Leme, Rafael Coradi Balestrassi, Pedro Paulo Univ Fed Itajuba Inst Ind Engn & Management BR-37500188 Itajuba MG Brazil

Today's modern industries have found a wide array of applications for optimization methods based on modeling with Robust Parameter Designs (RPD). Methods of carrying out RPD have thus multiplied. However, little attention has been given to the multiobjective optimization of correlated multiple responses using response surface with combined arrays. Considering this gap, this paper presents a multiobjective hybrid approach combining response surface methodology (RSM) with Principal Component Analysis (PCA) to study a multi-response dataset with an embedded noise factor, using a DOE combined array. How this approach differs from the most common approaches to RPD is that it derives the mean and variance equations using the propagation of error principle (POE). This comes from a control-noise response surface equation written with the most significant principal component scores that can be used to replace the original correlated dataset. Besides the dimensional reduction, this multiobjective programming approach has the benefit of considering the correlation among the multiple responses while generating convex Pareto frontiers to mean square error (MSE) functions. To demonstrate the procedure of the proposed approach, we used a bivariate case of AISI 52100 hardened steel turning employing wiper mixed ceramic tools. Theoretical and experimental results are convergent and confirm the effectiveness of the proposed approach. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： multiple objective programming Robust Parameter Design (RPD) Multivariate Mean Square Error (MMSE) Principal Component Analysis (PCA)

来源：评论

学校读者我要写书评

暂无评论

Two-group classification via a biobjective margin maximization model

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第3期173卷 746-761页

作者： Carrizosa, Emilio Martin-Barragan, Belen Univ Seville Dept Estadist & Invest Operat E-41012 Seville Spain

In this paper we propose a biobjective model for two-group classification via margin maximization, in which the margins in both classes are simultaneously maximized. The set of Pareto-optimal solutions is described, yielding a set of parallel hyperplanes, one of which is just the solution of the classical SVM approach. In order to take into account different misclassification costs or a priori probabilities, the ROC curve can be used to select one out of such hyperplanes by expressing the adequate tradeoff for sensitivity and specificity. Our result gives a theoretical motivation for using the ROC approach in case misclassification costs in the two groups are not necessarily equal. (c) 2005 Elsevier B.V. All rights reserved.

关键词： multiple objective programming support vector machines biobjective ROC curve classitication data mining

来源：评论

学校读者我要写书评

暂无评论

Weighted Multivariate Mean Square Error for processes optimization: A case study on flux-cored arc welding for stainless steel claddings

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2013年第3期226卷 522-535页

作者： Gomes, J. H. F. Paiva, A. P. Costa, S. C. Balestrassi, P. P. Paiva, E. J. Univ Fed Itajuba Inst Prod Engn & Management Itajuba MG Brazil

A mathematical programming technique developed recently that optimizes multiple correlated characteristics is the Multivariate Mean Square Error (MMSE). The MMSE approach has obtained noteworthy results, by avoiding the production of inappropriate optimal points that can occur when a method fails to take into account a correlation structure. Where the MMSE approach is deficient, however, is in cases where the multiple correlated characteristics need to be optimized with varying degrees of importance. The MMSE approach, in treating all responses as having the same importance, is unable to attribute the desired weights. This paper thus introduces a strategy that weights the responses in the MMSE approach. The method, called the Weighted Multivariate Mean Square Error (WMMSE), utilizes a weighting procedure that integrates Principal Component Analysis (PCA) and Response Surface Methodology (RSM). In doing so, WMMSE obtains uncorrelated weighted objective functions from the original responses. After being mathematically programmed, these functions are optimized by employing optimization algorithms. We applied WMMSE to optimize a stainless steel cladding application executed via the flux-cored arc welding (FCAW) process. Four input parameters and eight response variables were considered. Stainless steel cladding, which carries potential benefits for a variety of industries, takes low cost materials and deposits over their surfaces materials having anti-corrosive properties. Optimal results were confirmed, which ensured the deposition of claddings with defect-free beads exhibiting the desired geometry and demonstrating good productivity indexes. (C) 2012 Elsevier B.V. All rights reserved.

关键词： multiple objective programming Weighted Multivariate Mean Square Error (WMMSE) Stainless steel claddings Flux-cored arc welding (FCAW) Response Surface Methodology (RSM)

来源：评论

学校读者我要写书评

暂无评论

Integrating carrier selection with supplier selection decisions to improve supply chain security

引用

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2012年第5期19卷 711-732页

作者： Meixell, Mary J. Norbis, Mario Quinnipiac Univ Dept Management Hamden CT 06518 USA

Supply chain security is a major concern for logistics managers who have responsibility for inbound and outbound shipments to and from both domestic and international locations. We propose here that logistics decisions concerning security in the supply chain will be made more effectively when made in concert with decisions in related supply chain processes, especially supplier and carrier selection. Indeed, managers may minimize cost, transit time, and security risk by integrating decision processes internally, as well as with their carrier's and supplier's operations. Thus, we account for both intra-firm collaboration between logistics and purchasing managers, as well as inter-firm collaboration among buyers, suppliers, and carriers in a supply chain. In this paper, we propose a decision process that features a set of security rules and a multi-objective optimization model to accomplish this aim. We then provide an illustration to demonstrate the potential usefulness of these concepts in practice.

关键词： freight transportation logistics multiple objective programming optimization purchasing supply chain management

来源：评论

学校读者我要写书评

暂无评论

Corporate optimal production planning with varying environmental costs: A grey compromise programming approach

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2004年第1期155卷 68-95页

作者： Wu, CC Chang, NB Texas A&M Univ Dept Environm Engn Kingsville TX 78363 USA Acad Sinica Inst Stat Sci Taipei 115 Taiwan

Corporate environmental and resources management has become more strategically oriented when many pollution charges, environmental taxes, and resources conservation fees have been gradually imposing to the industry. The need for explicit consideration and incorporation of varying environmental costs within production-planning program is becoming critical to corporate management. This paper attempts to assess an optimal production-planning program in response to varying environmental costs in an uncertain environment. The optimal production strategy concerning numerous screening of possible production alternatives of dyeing cloth in a textile-dyeing firm in terms of market demand, resources availability, and impact of environmental costs is treated as an integral part of the multi-criteria decision-making framework based on the grey compromise programming approach. It covers not only the regular part of production costs and the direct income from product sales but also the emission/effluent charges and water resource fees reflecting part of the goals for internalization of external cost in a sustainable society. In particular, all the crucial variables in the model are addressed by interval expressions, the same as they are frequently applied in the grey systems theory, in support of a vital uncertainty assessment, which is much better suited for this particular study than other approaches. Research results demonstrate the applicability and significance of such an approach based on a case study. Industry looking for the competitive advantage of environmental management must be aware of the potential benefits from such an integrated production -planning program once the trend of increasing pollution charges, environmental taxes, and resources conservation fees remains. (C) 2003 Elsevier B.V. All rights reserved.

关键词： environmental management uncertainty analysis grey systems theory multiple objective programming optimal production planning

来源：评论

学校读者我要写书评

暂无评论

Robust multiobjective portfolio optimization: A minimax regret approach

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第1期262卷 299-305页

作者： Xidonas, Panos Mavrotas, George Hassapis, Christis Zopounidis, Constantin ESSCA Ecole Management 55 Quai Alphonse Le Gallo F-92513 Paris France Natl Tech Univ Athens Heroon Polytechneiou 9 Athens 15780 Greece Univ Cyprus Kallipoleos 75 CY-1678 Nicosia Cyprus Tech Univ Crete Sch Prod Engn & Management Univ Campus Khania 73100 Greece Audencia Business Sch 8 Route Joneliere F-44312 Nantes France

An efficient frontier in the typical portfolio selection problem provides an illustrative way to express the tradeoffs between return and risk. Following the basic ideas of modern portfolio theory as introduced by Markowitz, security returns are usually extracted from past data. Our purpose in this paper is to incorporate future returns scenarios in the investment decision process. For representative points on the efficient frontier, the minimax regret portfolio is calculated, on the basis of the aforementioned scenarios. These points correspond to specific weight combinations. In this way, the areas of the efficient frontier that are more robust than others are identified. The underlying key-contribution is related to the extension of the conventional minimax regret criterion formulation, in multiobjective programming problems. The validity of the approach is verified through an illustrative empirical testing application on the Eurostoxx 50. (C) 2017 Elsevier B.V. All rights reserved.

关键词： multiple objective programming Portfolio optimization Minimax regret Robustness

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：