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Modelling complex assemblies as a queueing network for lead time control

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2006年第1期174卷 150-168页

作者： Azaron, Amir Katagiri, Hideki Kato, Kosuke Sakawa, Masatoshi Hiroshima Univ Grad Sch Engn Dept Artificial Complex Syst Engn Higashihiroshima 7398527 Japan

In this paper we develop an open queueing network for optimal design of multi-stage assemblies, in which each service station represents a manufacturing or assembly operation. The arrival processes of the individual parts of the product are independent Poisson processes with equal rates. In each service station, there is a server with exponential distribution of processing time, in which the service rate is controllable. The transport times between the service stations are independent random variables with exponential distributions. By applying the longest path analysis in queueing networks, we obtain the distribution function of time spend by a product in the system or the manufacturing lead time. Then, we develop a multi-objective optimal control problem, in which the average lead time, the variance of the lead time and the total operating costs of the system per period are minimized. Finally, we use the goal attainment method to obtain the optimal service rates or the control vector of the problem. (c) 2005 Elsevier B.V. All rights reserved.

关键词： queueing control production multiple objective programming

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Cluster ensemble selection and consensus clustering: A multi-objective optimization approach

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第3期314卷 1065-1077页

作者： Aktas, Dilay Lokman, Banu Inkaya, Tulin Dejaegere, Gilles Ctr Ind Management KU Leuven Celestijnenlaan 300 B-3001 Leuven Belgium Univ Portsmouth Ctr Operat Res & Logist Sch Org Syst & People Portsmouth PO1 3DE England Bursa Uludag Univ Dept Ind Engn TR-16240 Nilufer Bursa Turkiye Univ Libre Bruxelles Serv Math Gest Blvd Triomphe CP 210-01 B-1050 Brussels Belgium

Cluster ensembles have emerged as a powerful tool to obtain clusters of data points by combining a library of clustering solutions into a consensus solution. In this paper, we address the cluster ensemble selection problem and design a multi -objective optimization -based solution framework to produce consensus solutions. Given a library of clustering solutions, we first design a preprocessing procedure that measures the agreement of each clustering solution with the other solutions and eliminates the ones that may mislead the process. We then develop a multi -objective optimization algorithm that selects representative clustering solutions from the preprocessed library with respect to size, coverage, and diversity criteria and combines them into a single consensus solution, for which the true number of clusters is assumed to be unknown. We conduct experiments on different benchmark data sets. The results show that our approach yields more accurate consensus solutions compared to full -ensemble and the existing approaches for most data sets. We also present an application on the customer segmentation problem, where our approach is used to segment customers and to find a consensus solution for each

关键词： multiple objective programming Cluster ensembles Ensemble selection Consensus clustering

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A new algorithm for solving planar multiobjective location problems involving the Manhattan norm

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第1期258卷 35-46页

作者： Alzorba, Shaghaf Guenther, Christian Popovici, Nicolae Tammer, Christiane Martin Luther Univ Halle Wittenberg Inst Math Fac Nat Sci 2 D-06099 Halle Saale Germany Univ Babes Bolyai Fac Math & Comp Sci Cluj Napoca 400084 Romania

This paper is devoted to the study of unconstrained planar multiobjective location problems, where distances between points are defined by means of the Manhattan norm. We characterize the nonessential objectives and, by eliminating them, we develop an effective algorithm for generating the whole set of efficient solutions as the union of a special family of rectangles and line segments. We prove the correctness of this algorithm, analyze its complexity, and present illustrative computational results obtained by a MATLAB-based implementation. (C) 2016 Elsevier B.V. All rights reserved.

关键词： multiple objective programming Location problem Manhattan norm Scalarization Nonessential objective

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Combined forecasts in portfolio optimization: A generalized approach

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COMPUTERS & OPERATIONS RESEARCH 2012年第4期39卷 805-819页

作者： Ustun, Ozden Kasimbeyli, Refail Izmir Univ Econ Fac Engn & Comp Sci Dept Ind Syst Engn TR-35330 Izmir Turkey Dumlupinar Univ Fac Engn Dept Ind Engn TR-43100 Kutahya Turkey

In this paper a general mathematical model for portfolio selection problem is proposed. By considering a forecasting performance according to the distributional properties of residuals, we formulate an extended mean-variance-skewness model with 11 objective functions. Returns and return errors for each asset obtained using different forecasting techniques, are combined in optimal proportions so as to minimize the mean absolute forecast error. These proportions are then used in constructing six criteria related to the mean, variance and skewness of return forecasts of assets in the future and forecasting errors of returns of assets in the past. The obtained multi-objective model is scalarized by using the conic scalarization method which guarantees to find all non-dominated solutions by considering investor preferences in non-convex multi-objective problems. The obtained scalar problem is solved by utilizing F-MSG algorithm. The performance of the proposed approach is tested on a real case problem generated on the data derived from Istanbul Stock Exchange. The comparison is conducted with respect to different levels of investor preferences over return, variance, and skewness and obtained results are summarized. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： multiple objective programming Risk management Global optimization Portfolio optimization Conic scalarization F-MSG algorithm

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Strong earthquakes and measurement performance of masonry and adobe structures

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STRUCTURAL ENGINEERING AND MECHANICS 2013年第1期47卷 99-118页

作者： Liu, Yanling Han, Qinkia Hainan Normal Univ Haikou 571158 Peoples R China Atilim Univ Dept Civil Engn TR-06830 Ankara Turkey

Earthquakes, which are unavoidable natural phenomena in Turkey, have often produced economic and social disaster. The latest destructive earthquakes happened inVan city. Van, Turkey, earthquakes with M = 7.2 occurredon 23 October 2011 at 13: 41 (local time), whose epicenterwas about 16 km north of Van (Tabanlivillage) and M = 5.6 on 9 November 2011 epicentered near the town of Edremitsouth of Van in eastern Turkey and caused the loss of lifeand heavy damages. Both earthquakes killed 644 peopleand 2608 people were injured. Approximately 4000 buildings collapsed or were seriously damaged. The majority ofthe damaged structures were seismically insufficient, unreinforced masonry and adobe buildings in rural areas. In thispaper, site surveys of the damaged masonry and adobe buildings are presented and the reasons for the caused damagesare discussed in detail.

关键词： earthquakes logistic model multiple objective programming Delphi method

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Redistribution of university budgets with respect to the status quo

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2004年第2期157卷 409-428页

作者： Tangian, A WSI Hans Bockler Stiftung D-40476 Dusseldorf Germany

University budgets are redistributed proportionally to five target criteria. The approach has been implemented in several models and applied to 15 North-Rhine Westfalia state universities. In the given paper, the problem is considered from the viewpoint of the general techniques for constructing objective functions for evaluating alternatives. It enables us to formulate three additional models aimed at best respecting the status quo: with minimizing absolute changes of actual budgets, with minimizing relative changes of actual budgets, and with minimizing changes of individual rules for budget accounting. The models are based on either linear, or quadratic objective functions, the latter being considered under several optional assumptions: local monotonicity, global monotonicity, concavity, and convexity. The paper is illustrated with computer results. (C) 2003 Elsevier B.V. All rights reserved.

关键词： decision support systems multiple criteria analysis polynomial regression in several variables multiple objective programming quadratic programming budgeting resource allocation

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PLANNING RELOCATION OF PEOPLE FOR DEVELOPING SURFACE MINES IN DENSELY POPULATED AREAS: OPTIMIZATION OF multiple objectiveS

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2011年第5期28卷 563-583页

作者： Zahir, Sajjad Sarker, Ruhul Univ Lethbridge Fac Management Lethbridge AB T1K 3M4 Canada Univ New S Wales Australian Def Force Acad Sch Engn & Informat Technol Canberra ACT 2600 Australia

Surface mining, often adopted for exploiting natural resources all over the world, is a major subject of debate as it causes major environmental impacts. It not only adversely alters the landscape but it also seriously hampers the traditional living conditions of numerous inhabitants, who may be displaced against their wishes without receiving necessary compensation. In this paper, goal programming is combined with the analytic hierarchy process to determine optimal decisions for the planned relocation of people where surface mining may take place in a densely populated environment, while addressing multiple conflicting objectives. The combined approach is illustrated with a numerical example highlighting its usage in other decision problems.

关键词： Goal programming environment multiple criteria analysis multiple objective programming OR in developing countries OR in strategic planning

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Time-cost trade-off via optimal control theory in Markov PERT networks

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ANNALS OF OPERATIONS RESEARCH 2007年第1期150卷 47-64页

作者： Azaron, Amir Katagiri, Hideki Sakawa, Masatoshi Hiroshima Univ Grad Sch Engn Hiroshima 7398527 Japan Dalhousie Univ Dept Ind Engn Halifax NS Canada Univ Bu Ali Sina Fac Engn Dept Ind Engn Hamadan Iran

We develop a new analytical model for the time-cost trade-off problem via optimal control theory in Markov PERT networks. It is assumed that the activity durations are independent random variables with generalized Erlang distributions, in which the mean duration of each activity is a non-increasing function of the amount of resource allocated to it. Then, we construct a multi-objective optimal control problem, in which the first objective is the minimization of the total direct costs of the project, in which the direct cost of each activity is a non-decreasing function of the resources allocated to it, the second objective is the minimization of the mean of project completion time and the third objective is the minimization of the variance of project completion time. Finally, two multi-objective decision techniques, viz, goal attainment and goal programming are applied to solve this multi-objective optimal control problem and obtain the optimal resources allocated to the activities or the control vector of the problem.

关键词： project management multiple objective programming optimal control theory Markov processes

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On the use of the distance in reference point-based approaches for multiobjective optimization

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ANNALS OF OPERATIONS RESEARCH 2015年第1期235卷 559-579页

作者： Luque, Mariano Ruiz, Ana B. Saborido, Ruben Marcenaro-Gutierrez, Oscar D. Univ Malaga Dept Appl Econ Math E-29071 Malaga Spain Ecole Polytech Polytech Montreal Researchers Software Engn Montreal PQ H3C 3A7 Canada Univ Malaga Dept Appl Econ Stat & Econometr E-29071 Malaga Spain

Reference point-based methods are very useful techniques for solving multiobjective optimization problems. In these methods, the most commonly used achievement scalarizing functions are based on the Tchebychev distance (minmax approach), which generates every Pareto optimal solution in any multiobjective optimization problem, but does not allow compensation among the deviations to the reference values given that it minimizes the value of the highest deviation. At the same time, for any , compromise programming minimizes the distance to the ideal objective vector from the feasible objective region. Although the ideal objective vector can be replaced by a reference point, achievable reference points are not supported by this approach, and special care must be taken in the unachievable case. In this paper, for , we propose a new scheme based on the distance, in which different single-objective optimization problems are designed and solved depending on the achievability of the reference point. The formulation proposed allows different compensation degrees among the deviations to the reference values. It is proven that, in the achievable case, any optimal solution obtained is efficient, and, in the unachievable one, it is at least weakly efficient, although it is assured to be efficient if an augmentation term is added to the new formulation. Besides, we suggest an interactive algorithm where the new formulation is embedded. Finally, we show the empirical advantages of the new formulation by its application to both numerical problems and a real multiobjective optimization problem, for achievable and unachievable reference points.

关键词： Reference point multiple objective programming Compromise programming Distance-based multiobjective optimization approaches

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An extended goal programming model for site selection in the offshore wind farm sector

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ANNALS OF OPERATIONS RESEARCH 2016年第1-2期245卷 121-135页

作者： Jones, Dylan F. Wall, Graham Univ Portsmouth Dept Math Ctr Operat Res & Logist Lion Terrace Portsmouth PO1 3HF Hants England

This paper presents an application of extended goal programming in the field of offshore wind farm site selection. The strategic importance of offshore shore wind farms is outlined, drawing on the case of the United Kingdom proposed round three sites as an example. The use of multi-objective modelling methodologies for the offshore wind farm sector is reviewed. The technique of extended goal programming is outlined and its flexibility in combining different decision maker philosophies described. An extended goal programming model for site selection based on the United Kingdom future sites is then developed and a parametric analysis undertaken at the meta-objective level. The results are discussed and conclusions are drawn.

关键词： multiple objective programming Extended goal programming Offshore wind Renewable energy

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