Showing papers on "Goal programming published in 2003"

An integrated approach for supplier selection

Abstract: Competitive international business environment has forced many firms to focus on supply chain management to cope with highly increasing competition. Hence, supplier selection process has gained importance recently, since most of the firms have been spending considerable amount of their revenues on purchasing. The supplier selection problem involves conflicting multiple criteria that are tangible and intangible. Hence, the purpose of this study is to propose an integrated model for supplier selection. In order to achieve this purpose, supplier selection problem has been structured as an integrated lexicographic goal programming (LGP) and analytic hierarchy process (AHP) model including both quantitative and qualitative conflicting factors. The application process has been accomplished in a food company established in Istanbul, Turkey. In this study, the model building, solution and application processes of the proposed integrated model for supplier selection have been presented.

Decision Methods for Forest Resource Management

Abstract: Preface Introduction Principles of Linear Programming: Formulations Principles of Linear Programming: Solutions: Even-Aged Management: A First Model Area - and Volume-Control Management with Linear Programming: A Dynamic Model of the Even-Aged Forest Economic Objectives and Environmental Policies for Even-Aged Forests Managing the Uneven-Aged Forest with Linear Programming Economic and Environmental Management of Uneven-Aged Forests Multiple Objectives Management with Goal Programming Forest Resource Programming Models with Integer Variables Project Management with CPM/PERT Multistage Decision Making with Dynamic Programming Simulation of Uneven-Aged Stand Management Simulation of Even-Aged Forest Management Projecting Forest Landscape and Income Under Risk with Markov Chains Optimizing Forest Income and Biodiversity with Markov Decision Processes Analysis of Forest Resource Investments Econometric Analysis and Forecasting of Forest Product markets Appendix A: Compounding and Discounting Appendix B: Elements of Matrix Algebra

Multiobjective optimal power flows to evaluate voltage security costs in power networks

Abstract: In this paper, new optimal power flow (OPF) techniques are proposed based on multiobjective methodologies to optimize active and reactive power dispatch while maximizing voltage security in power systems. The use of interior point methods together with goal programming and linearly combined objective functions as the basic optimization techniques are explained in detail. The effects of minimizing operating costs, minimizing reactive power generation, and/or maximizing loading margins are then compared in both a 57-bus system and a 118-bus system, which are based on IEEE test systems and modeled using standard power flow models. The results obtained using the proposed mixed OPFs are compared and analyzed to suggest possible ways of costing voltage security in power systems.

Evolutionary multiobjective optimization using a cultural algorithm

Abstract: In this paper, we present the first proposal to use a cultural algorithm to solve multiobjective optimization problems. Our proposal uses evolutionary programming, Pareto ranking and elitism (i.e., an external population). The approach proposed is validated using several examples taken from the specialized literature. Our results are compared with respect to the NSGA-II, which is an algorithm representative of the state-of-the-art in evolutionary multiobjective optimization. The performance of our approach indicates that cultural algorithms are a viable alternative for multiobjective optimization.

Goal Programming in the Period 1990–2000

Abstract: This chapter presents a bibliography of goal programming for the period 1990–2000. Goal programming is introduced and the main variants are defined. An analysis of applications by field is given. A survey of advances in various goal programming extension areas is conducted. The integration and combination of goal programming with other solution, analysis, and modelling techniques is examined. Conclusions are drawn and suggestions for future research directions are made. A list of over 280 references is presented.

MultiObjective Programming and Goal Programming

Abstract: This book gives the reader an insight into the state of the art in the field of multiobjective (linear, nonlinear and combinatorial) programming, goal programming and multiobjective metaheuristics. The 26 papers describe all relevant trends in this fields of research . They cover a wide range of topics ranging from theoretical investigations to algorithms, dealing with uncertainty, and applications to real world problems such as engineering design, water distribution systems and portfolio selection. The book is based on the papers of the seventh international conference on multiple objective programming and goal programming (MOPGP06).

Multi-site aggregate production planning with multiple objectives: A goal programming approach

Abstract: This paper addresses the problem of aggregate production planning (APP) for a multinational lingerie company in Hong Kong. The multi-site production planning problem considers the production loading plans among manufacturing factories subject to certain restrictions, such as production import/export quotas imposed by regulatory requirements of different nations, the use of manufacturing factories/locations with regard to customers' preferences, as well as production capacity, workforce level, storage space and resource conditions of the factories. In this paper, a multi-objective model is developed to solve the production planning problems, in which the profit is maximized but production penalties resulting from going over/under quotas and the change in workforce level are minimized. To enhance the practical implications of the proposed model, different managerial production loading plans are evaluated according to changes in future policy and situation. Numerical results demonstrate the robustness and effectiveness of the developed model.

Determining attribute weights using mathematical programming

Abstract: Group decisions are an important element of successful knowledge management in organizations. Such decisions are difficult to make, however, especially when they involve a large set of attributes that require decision-makers to develop rankings. This paper presents a goal programming model for determining constrained regression estimates of attribute weights. The model is developed using pair-wise comparison ratings that are derived by using triads of the attributes. In addition, metrics are presented for measuring individual and group consensus. A specific application to the health care industry is presented to illustrate results that are obtained from the model.

A fuzzy goal programming procedure for solving quadratic bilevel programming problems

Abstract: This article presents a fuzzy goal programming (FGP) procedure for solving quadratic bilevel programming problems (QBLPP). In the proposed approach, the membership functions for the defined fuzzy objective goals of the decision makers (DM) at both the levels are developed first. Then, a quadratic programming model is formulated by using the notion of distance function minimizing the degree of regret to satisfaction of both DMs. At the first phase of the solution process, the quadratic programming model is transformed into an equivalent nonlinear goal programming (NLGP) model to maximize the membership value of each of the fuzzy objective goals on the extent possible on the basis of their priorities in the decision context. Then, at the second phase, the concept of linear approximation technique in goal programming is introduced for measuring the degree of satisfaction of the DMs at both the levels by arriving at a compromised decision regarding the optimality of two different sets of decision variables controlled separately by each of them. A numerical example is provided to illustrate the proposed approach. © 2003 Wiley Periodicals, Inc.

Multi-objective programming and goal programming : theory and applications

Abstract: I: Invited Papers.- Multiple Objective Combinatorial Optimization - A Tutorial.- Analysis of Trends in Distance Metric Optimisation Modelling for Operational Research and Soft Computing.- MOP/GP Approaches to Data Mining.- Computational Investigations Evidencing Multiple Objectives in Portfolio Optimization.- Behavioral Aspects of Decision Analysis with Application to Public Sectors.- Optimization Models for Planning Future Energy Systems in Urban Areas.- Multiple Objective Decision Making in Past, Present, and Future.- Dynamic Multiple Goals Optimization in Behavior Mechanism.- II: General Papers - Theory.- An Example-Based Learning Approach to Multi-Objective Programming.- Support Vector Machines using Multi Objective Programming.- On the Decomposition of DEA Inefficiency.- An Approach for Determining DEA Efficiency Bounds.- An Extended Approach of Multicriteria Optimization for MODM Problems.- The Method of Elastic Constraints for Multiobjective Combinatorial Optimization and its Application in Airline Crew Scheduling.- Some Evaluations Based on DEA with Interval Data.- Possibility and Necessity Measures in Dominance-based Rough Set Approach.- Simplex Coding Genetic Algorithm for the Global Optimization of Nonlinear Functions.- On Minimax and Maximin Values in Multicriteria Games.- Backtrack Beam Search for Multiobjective Scheduling Problem.- Cones to Aid Decision Making in Multicriteria Programming.- Efficiency in Solution Generation Based on Extreme Ray Generation Method for Multiple Objective Linear Programming.- Robust Efficient Basis of Interval Multiple Criteria and Multiple Constraint Level Linear Programming.- An Interactive Satisficing Method through the Variance Minimization Model for Fuzzy Random Multiobjective Linear Programming Problems.- On Saddle Points of Multiobjective Functions.- An Application of Fuzzy Multiobjective Programming to Fuzzy AHP.- On Affine Vector Variational Inequality.- Graphical Illustration of Pareto Optimal Solutions.- An Efficiency Evaluation Model for Company System Organization.- Stackelberg Solutions to Two-Level Linear Programming Problems with Random Variable Coefficients.- On Inherited Properties for Vector-Valued Multifunctions.- Multicriteria Expansion of a Competence Set Using Genetic Algorithm.- Comparing DEA and MCDM Method.- Linear Coordination Method for Multi-Objective Problems.- Experimental Analysis for Rational Decision Making by Aspiration Level AHP.- Choquet Integral Type DEA.- Interactive Procedures in Hierarchical Dynamic Goal Programming.- Solution Concepts for Coalitional Games in Constructing Networks.- Multi-Objective Facility Location Problems in Competitive Environments.- Solving Portfolio Problems Based on Meta-Controled Boltzmann Machine.- Tradeoff Directions and Dominance Sets.- A Soft Margin Algorithm Controlling Tolerance Directly.- An Analysis of Expected Utility Based on Fuzzy Interval Data.- On Analyzing the Stability of Discrete Descriptor Systems via Generalized Lyapunov Equations.- Solving DEA via Excel.- III: General Papers - Applications.- Planning and Scheduling Staff Duties by Goal Programming.- An Interactive Approach to Fuzzy-based Robust Design.- A Hybrid Genetic Algorithm for solving a capacity Constrained Truckload Transportation with crashed customer.- A Multi-Objective Programming Approach for Evaluating Agri-Environmental Policy.- Improve the Shipping Performance of Build-to-ORder (BTO) Product in Semiconductor Wafer Manufacturing.- Competence Set Expansion for Obtaining Scheduling Plans in Intelligent Transportation Security Systems.- DEA for Evaluating the Current-period and Cross-period Efficiency of Taiwan's Upgraded Technical Institutes.- Using DEA of REM and EAM for Efficiency Assessment of Technology Institutes Upgraded from Junior Colleges: The Case in Taiwan.- The Comprehensive Financial Risk Management in a Bank - Stochastic Goal Programming Optimization.- The Effectiveness of the Balanced Scorecard Framework for E-Commerce.- A Study of Variance of Locational Price in a Deregulated Generation Market.- Pseudo-Criterion Approaches to Evaluating Alternatives in Mangrove Forests Management.- Energy-Environment-Cost Tradeoffs in Planning Energy Systems for an Urban Area.- DEA Approach to the Allocation of Various TV Commercials to Dayparts.- Analyzing Alternative Strategies of Semiconductor Final Testing.- A Discrete-Time European Options Model under Uncertainty in Financial Engineering.- Multipurpose Decision-Making in House Plan by Using AHP.

Decision support for the academic library acquisition budget allocation via circulation database mining

Abstract: Many approaches to decision support for the academic library acquisition budget allocation have been proposed to diversely reflect the management requirements. Different from these methods that focus mainly on either statistical analysis or goal programming, this paper introduces a model (ABAMDM, acquisition budget allocation model via data mining) that addresses the use of descriptive knowledge discovered in the historical circulation data explicitly to support allocating library acquisition budget. The major concern in this study is that the budget allocation should be able to reflect a requirement that the more a department makes use of its acquired materials in the present academic year, the more it can get budget for the coming year. The primary output of the ABAMDM used to derive weights of acquisition budget allocation contains two parts. One is the descriptive knowledge via utilization concentration and the other is the suitability via utilization connection for departments concerned. An applicat-ion to the library of Kun Shan University of Technology was described to demonstrate the introduced ABAMDM in practice.

Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem

Abstract: Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decision-making problems Recent developments in this field focus on the design of allocation plans that utilize mathematical optimization techniques These techniques, often referred to as multi criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications In this paper, it is demonstrated how both Simulated annealing, a heuristic algorithm, and Goal Programming techniques can be used to solve high-dimensional optimization problems for multi-site land use allocation (MLUA) problems The optimization models both minimize development costs and maximize spatial compactness of the allocated land use The method is applied to a case study in The Netherlands

Transitive approximation to pairwise comparison matrices by using interval goal programming

Abstract: Paired comparison is a very popular method for establishing the relative importance of n objects, when they cannot be directly rated. The challenge faced by the pairwise comparison method stems from some missing properties in its associated matrix. In this paper, we focus on the following general problem: given a non-reciprocal and inconsistent matrix computing intransitivities, what is its associated ranking (defined by importance values)? We propose to use inconsistencies as a source of information for obtaining importance values. For this purpose, a methodology with a decomposition and aggregation phase is proposed. Interval Goal Programming will be a useful tool for implementing the aggregation process defined in the second phase.

Modeling knowledge: Model-based decision support and soft computations

Abstract: This chapter provides an overview of model-based support for modern decision making. It starts with discussing basic elements of decision making process, including characteristics of complex decision problems, concepts of rationality, and various requirements for model-based support at different stages of decision making process. Then the characteristics of models, and of modeling processes aimed at decision-making support for complex problems are presented. In this part guidelines for model specification and instantiation are illustrated by an actual complex model. This is followed by a discussion of modern methods of model analysis, which include a more detailed discussion of reference point optimization methods, and an outline of methods for sensitivity analysis, and of softly constrained inverse simulation. Finally, an overview of architecture of model-based decision support system is presented.

Integrating scenario planning and goal programming

Abstract: This paper concerns the integration of goal programming and scenario planning as an aid to decision making under uncertainty. Goal programming as a methodology emphasises the resolution of conflict among criteria; scenario planning focuses on the treatment of uncertainty relating to future states of the world. Integrating the two methodologies is based on the simple formulation of a super-goal programme consisting of one scenario-specific goal program in each scenario. Issues relating to the structuring of the super-problem, aggregation both within and over scenarios, and the incorporation of probabilistic information are discussed. Copyright © 2005 John Wiley & Sons, Ltd.

Human Resource Allocation in a CPA Firm: A Fuzzy Set Approach

Abstract: The review of existing human resource allocation models for a CPA firm shows that there are major shortcomings in the previous mathematical models. First, linear programming models cannot handle multiple objective human resource allocation problems for a CPA firm. Second, goal programming or multiple objective linear programming (MOLP) cannot deal with the organizational differentiation problems. To reduce the complexity in computing the trade-offs among multiple objectives, this paper adopts a fuzzy set approach to solve human resource allocation problems. A solution procedure is proposed to systematically identify a satisfying selection of possible staffing solutions that can reach the best compromise value for the multiple objectives and multiple constraint levels. The fuzzy solution can help the CPA firm make a realistic decision regarding its human resource allocation problems as well as the firm's overall strategic resource management when environmental factors are uncertain.

Measuring and evaluating efficiency and effectiveness using goal programming and data envelopment analysis in a fuzzy environment

Abstract: Generally, in most situations optimal achievement of multiple goals is rarely possible for crisp mathematical programming techniques. In such cases, a compromise achievement of goals that leads to a satisfycing solution rather than an optimal solution bears more relevance. The present research introduces a Fuzzy Goal Data Envelopment Analysis (Fuzzy GoDEA) framework to measure and evaluate the goals of efficiency and effectiveness in a fuzzy environment. Fuzzy GoDEA accommodates crisp input and output data but allows imprecise specification of the aspiration levels for the efficiency and effectiveness goals. A membership function is defined for each fuzzy constraint associated with the efficiency and effectiveness goals and represents the degree of achievement of that constraint. Further, the Fuzzy GoDEA framework is extended into several variations that (i) allow the assignment of relative importance to the goals of efficiency and effectiveness and (ii) model scenarios where one of the goals of efficiency and effectiveness is crisp and the other fuzzy. The Fuzzy GoDEA framework is implemented for a newspaper preprint insertion process (NPIP).

Integration of Two Multiobjective Optimization Methods for Nonlinear Problems

Abstract: In this paper, we bring together two existing methods for solving multiobjective optimization problems described by nonlinear mathematical models and create methods that benefit from both heir strengths. We use the Feasible Goals Method and the NIMBUS method to form new hybrid approaches. The Feasible Goals Method (FGM) is a graphic decision support tool that combines ideas of goal programming and multiobjective methods. It is based on the transformation of numerical information given by mathematical models into a variety of feasible criterion vectors (that is, feasible goals). Visual interactive display of this variety provides information about the problem that helps the decision maker to detect the limits of what is possible. Then, the decision maker can identify a preferred feasible criterion vector on the graphic display. NIMBUS is an interactive multiobjective optimization method capable of solving nonlinear and even nondifferentiable and nonconvex problems. The decision maker can iteratively evalua...

Linear physical programming for production planning optimization

Abstract: Production planning plays a central role in the successful management of any production-oriented company. Production planning is typically multiobjective in nature and the management thereof generally consists of balancing/resolving many conflicting objectives. Previous works have shown that successful production planning can be achieved using multiobjective optimization. In this paper, a production-planning model conducive to optimization is developed and used with the preference-based optimization method Linear Physical Programming (LPP). Machine yield rates and production time are important components of the proposed model and examples that illustrate the optimization process. The key contribution of this work is in the application of LPP to a newly developed production planning model. The benefit of LPP is that it capitalizes on latent human experience and previous design knowledge when such is available. Otherwise, LPP effectively helps the designer explore the design space.

A new strategic information technology investment model

Abstract: Many of the financial instruments used in classic investment analysis do not apply to typical information technology investment decision making because of the multi‐criteria and multi‐objective nature of the problem. This is particularly true when integrating strategic, tactical, and operations planning objectives in the decision. One approach for making IT investment decisions is a multi‐objective goal programming (GP) model proposed by Talluri in 2000. The purpose of our paper is twofold: to demonstrate how a simple ranking/scoring method can be used in place of the more involved Talluri GP modeling approach if only a solution is required; and, in decision situations where solution justification is desired, to explain how GP extension methodologies can be incorporated into the analysis to generate information to determine a solution’s reliability and identify economic tradeoffs that can be used to improve an existing solution.

Consistency-driven approximation of a pairwise comparison matrix

Abstract: The pairwise comparison method is an interesting technique for building a global ranking from binary comparisons. In fact, some web search engines use this method to quantify the importance of a set of web sites. The purpose of this paper is to search a set of priority weights from the preference information contained in a general pairwise comparison matrix; i.e., a matrix without consistency and reciprocity properties. For this purpose, we consider an approximation methodology within a distance-based framework. In this context, Goal Programming is introduced as a flexible tool for computing priority weights.