Showing papers on "Goal programming published in 1978"
TL;DR: This model, its history, methods of solution and list some recent applications are examined, hoping the reader will appreciate the rather general nature of the field, along with the relative simplicity of model development and solution.
Abstract: Goal programming is a relatively new tool that has been proposed as a model and approach for the analysis of problems involving multiple, conflicting objectives. In this paper we examine this model, its history, methods of solution and list some recent applications. Hopefully, the reader will appreciate the rather general nature of the field, along with the relative simplicity of model development and solution.
218 citations
TL;DR: A model is suggested which seems to be suited to map appropriately fuzzy and subjective phenomena and which is flexible enough to incorporate several criteria (objective functions) simultaneously.
Abstract: Mathematical Programming models have been suggested as a tool for optimal media selection. In order to accommodate several objective functions goal programming models have been put forward. It seems, however, that these models are not yet operational and efficient enough to be used in practice.
66 citations
TL;DR: An efficient algorithm for solving linear goal programming problems using partitioning and elimination procedures is presented and preliminary results indicate that the partitioning algorithm is superior to the existing methods for solving goal Programming problems.
Abstract: An efficient algorithm for solving linear goal programming problems using partitioning and elimination procedures is presented. The algorithm takes advantage of the definition of ordinal preemptive factors in the objective function inherent in most goal programming formulations. Preliminary results indicate that the partitioning algorithm is superior to the existing methods for solving goal programming problems.
56 citations
TL;DR: In this article, the authors address the problem of goal conflicts in the portfolio selection of dual-purpose funds, and propose an extension of standard methodology, in terms of the development of a goal programming model in conceptual form, which can be applied for the resolution of inherent clash of interests.
Abstract: STANDARD PORTFOLIO SELECTION TECHNIQUES are typically characterized by motivational assumptions of unified goals or objectives [8]. Consequently, their immediate relevance to real-world situations, usually marked by the presence of several conflicting goals, is at best limited. Nevertheless, with appropriate extensions the standard techniques can form the basis for accommodating multiple goals. The present study is addressed to the problem of goal conflicts in the portfolio selection of Dual-Purpose Funds, and proposes an extension of standard methodology, in terms of the development of a Goal Programming model in conceptual form, which can be applied for the resolution of inherent clash of interests. Section II presents the organizational structure of Dual-Purpose Funds, their performance record, and the potential conflict of interests. The theoretical foundations of goal programming are discussed in Section III. The basic model and other possible variations for portfolio selection are developed in Section IV, while some suggested extensions are offered in Section V.
53 citations
01 Jan 1978
TL;DR: The past decade has seen a dramatic increase in research on all main areas of multiple criteria decision-making, including formal models of multicriterion choice, multicriteria evaluation theories, and multi-criteria assessment methodologies as mentioned in this paper.
Abstract: The past decade has seen a dramatic increase in research on all main areas of multiple criteria decision making, including formal models of multicriterion choice, multicriterion evaluation theories, and multicriterion assessment methodologies.
50 citations
TL;DR: It is pointed out how the preemptive goal-programming approach is incompatible with utility preferences and the tendency of optimal solutions for standard linear goal programs to occur at extreme points is observed.
Abstract: After first formulating the problem of the Marine Environmental Protection program of the Coast Guard as a multiple-objective linear program, we investigate the applicability and limitations of goal programming. We point out how the preemptive goal-programming approach is incompatible with utility preferences. Then we observe the tendency of optimal solutions for standard linear goal programs to occur at extreme points. We also note problems of more general approaches, such as dealing with additively separable approximations to preferences.
33 citations
30 citations
TL;DR: The formulation of a goal programming model for analysis of the transshipment problem, where multiple conflicting objectives must be considered, is presented and the solution to the problem is presented.
28 citations
TL;DR: A goal programming model for coordinating the production of an aggregate schedule which is to be fed into the detailed scheduling package currently employed is developed and discussed.
Abstract: The paper introduces mi overall scheduling problem. One crucial aspect is identified; this is the production of an aggregate schedule which is to be fed into the detailed scheduling package currently employed. The problem is seen to be that of achieving a balance between a smooth work-load on the factory floor and matching production with promised delivery dates. A goal programming model for this coordination is developed and discussed. Numerical examples illustrating the approach are presented, and computational experience is discussed.
28 citations
TL;DR: A goal programming model is developed and demonstrated via a case example of the multi-product scheduling problem when multiple objectives exist and the various solution approaches to the problem are presented.
24 citations
01 Jan 1978
TL;DR: In this article, the authors developed and demonstrated interactive integer goal programming methods for multiple objective problems through a real-world application example, which allows not only a simple way to derive an integer solution to the problem but also provides a complete sensitivity analysis of the model.
Abstract: Goal programming has received a great deal of attention during the past several years as a management decision making tool for problems that involve multiple conflicting objectives. One area of goal programming which requires further development is the integer solution methodology. The purpose of this paper is the development and demonstration of interactive integer goal programming methods for multiple objective problems through a real-world application example. The interactive approach allows not only a simple way to derive an integer solution to the problem but it also provides a complete sensitivity analysis of the model.
TL;DR: This paper demonstrates how goal programming (GP) can be used to incorporate considerations other than project completion time and total project cost into the typical CPM problem.
Abstract: This paper demonstrates how goal programming (GP) can be used to incorporate considerations other than project completion time and total project cost into the typical CPM problem. In particular, factors such as share of the market, completion time of individual jobs, contractual agreements, and scarcity of resources such as men, materials and machines are taken into consideration. An example is provided to illustrate the use of the GP approach in a CPM problem.
TL;DR: This paper shows that a certain class of manpower systems that are often modelled using goal programming can also be modelled as capacitated transshipment problems through the use of generalized linear programming codes.
Abstract: This paper shows that a certain class of manpower systems that are often modelled using goal programming can also be modelled as capacitated transshipment problems. The goal programming structure can be preserved in most cases through careful definition of the flow-cost function and through the use of multiple arcs in the network. This latter feature is made practical through the use of advanced network codes, such as GNET, that are now available. Solution times and costs are significantly lower than those obtained with the original goal programming formulation through the use of generalized linear programming codes.
TL;DR: In this paper, the authors consider the validity of substituting a linear goal for a fractional goal in a mathematical program and provide a simple geometric interpretation that contrasts the essential differences between the two programs.
Abstract: In this note we consider the validity of substituting a linear goal for a fractional goal in a mathematical program and provide a simple geometric interpretation that contrasts the essential differences between the two programs.
TL;DR: In this paper, the authors introduce the subjective preferences of decisionmakers into multiobjective programming models and compare the characteristics of goal programming and multi-objective linear programming in dealing with multobjective problems.
Abstract: * In recent years, there has been much interest in models of multiobjective decision-making. The finance literature reflects this with the formulation of problems in capital budgeting [6, 8, 13], working capital management [10], portfolio selection [7, ch. 9], and commercial bank management [2, 4, 5, 9, 11] as multiobjective decision-making problems. Given multiple conflicting objectives, resolution of any planning problem depends on subjective judgments and relative preferences of decision-makers. Unfortunately, how to include managerial preferences in normative decision models, and the effect of these preferences on optimal solutions, has scarcely been explored. Moreover, there has been little if any research on the relative merits of various programming techniques in dealing with multiobjective problems. The purposes of this paper are to discuss introducing the subjective preferences of decisionmakers into multiobjective programming models and to compare the characteristics of goal programming and multiobjective linear programming in dealing with multiobjective problems. Multiobjective Problems and Programming Techniques
TL;DR: Goal programming, a technique which has been highly successful in other problems involving multiple objectives, is the technique employed in the problem of deciding which books and standing orders to purchase from a list submitted by a given department, division or school of a university.
TL;DR: In this article, a goal programming model for project selection when both profit and non-profit motivated projects are in competition for scarce resources is described and demonstrated in the context of large production operations.
Abstract: Managers of large production operations are often confronted with the necessity to invest in capital projects whose income generating capacity is not the prime consideration for selection. Examples of this type of investment include projects which satisfy safety, environmental, union and/or consumer requirements placed on the firm. This paper describes and demonstrates a goal programming model for project selection when both profit and nonprofit motivated projects are in competition for scarce resources.
01 Jan 1978
TL;DR: Goal programming provides the decision maker (DM) with one decision vector, but does not help the DM learn his preferences, since it does not explore the nondominated set.
Abstract: Goal programming provides the decision maker (DM) with one decision vector, but does not help the DM learn his preferences, since it does not explore the nondominated set Proponents of goal programming claim that the DM has a multiattribute utility function which is assumed to be separable, additive and stable over decision iterations These are extremely restrictive assumptions In addition, the way the priority weights drive a linear equation system is very hard to characterize
01 Dec 1978
TL;DR: The most important results concerning the stochastic dynamic decision processes with finite state and action spaces can be handled by policy and value iteration, both typical dynamic programming techniques, as well as by linear programming.
Abstract: As has been known for a long time, stochastic dynamic decision processes with finite state and action spaces can be handled by policy and value iteration, both typical dynamic programming techniques, as well as by linear programming. In the present paper, the most important results concerning the latter are reported and an outlook on more general settings is given.
TL;DR: In this paper, an integer (0-1) goal programming model for the recreational allocation problem is described and the model results specify the facilities which should be constructed that best meet the conflicting goals.
Abstract: Urban planners are often involved in the determination of where recreational facilities (i.e. pools, gymnasia, tennis courts, etc.) should be located within the city. This problem is complicated by the planners' desire to realize certain goals in the allocation process. They desire to build only facilities for which there are sufficient construction funds and which can be operated within a predetermined budget. In addition they desire to satisfy the demands of the residents of the city for different facilities. However, these demands are often conflicting since many urban areas are somewhat segregated with the inner city being predominantly minority/lower income and the outer city consisting of white/upper income groups. These different groups enjoy different types of recreation, and, thus, demand different facilities. Since this is basically an allocation problem with multiple conflicting objectives, goal programming surfaces as an appropriate solution technique. This paper describes an integer (0-1) goal programming model for the recreational allocation problem and demonstrates its use via a case example. The model results specify the facilities which should be constructed that best meet the conflicting goals.
TL;DR: In this paper, a hybrid model which combines the goals-achievement matrix approach with goal programming is described, which allows for the explicit incorporation of the different objectives and values of the partners to the decision-making process and other affected parties in the determination of the preferred set of policies.
Abstract: The paper describes a hybrid model which combines the goals-achievement matrix approach with goal programming. It allows for the explicit incorporation of the different objectives and values of the partners to the decisionmaking process and other affected parties in the determination of the preferred set of policies. In addition, it can deal with diminishing utility and the lexicographic ordering of objectives. The use of the model is demonstrated with a hypothetical example of a neighbor hood rehabilitation program. The application of sensivity analysis in the decisionmaking process is discussed also.
TL;DR: In this paper, the development of cost estimation relations via goal programming is discussed, with a focus on cost estimation in the context of cost estimating relationships via goal-programming and cost estimation.
Abstract: (1978). The Development of Cost Estimating Relationships Via Goal Programming. The Engineering Economist: Vol. 24, No. 1, pp. 37-48.
01 Jan 1978
TL;DR: This paper discusses a multi-level system of goal programming models with embedded Markoff processes—a master model for evaluating corporate goals and a “coherence” model for local personnel management decisions.
Abstract: Manpower planning for equal employment opportunity (EEO) must ensure a representation of social groups within the organization that matches their representation in the environment surrounding that organization. This paper discusses a multi-level system of goal programming models with embedded Markoff processes—a master model for evaluating corporate goals and a “coherence” model for local personnel management decisions. Both models have unique state-of-the-art features such as dual goal sets, the incorporation of flexibility options, the use of “bridge positions” and the use of piece-wise linear goal functionals in a capacitated distribution model format. A brief description of each model is given, followed by a discussion of some issues surrounding the process of goal setting and attendant issues of reporting and accountability.
TL;DR: It is the hope of the authors that this model will provide management with an additional decision-making tool for implementation of multiple corporate objectives through the use of integer goal programming.
TL;DR: In this article, a set of integrated planning models for a school board in a public school system were developed. But they were not useful to implement for reasons outlined in the paper.
Abstract: This paper relates experience in the development of a set of integrated planning models for a school board in a public school system. Three modules were developed. An enrolment projection module utilizes a modified Markov transition matrix (augmented by adaptive exponential smoothing models to forecast flows into the system). A program review module operates in interactive mode as a deterministic simulation to generate alternative budgets in a ‘planning-programming-budgeting’ context. A resource planning module was produced as an optimizing goal programming formulation, but was not found useful to implement for reasons outlined in the paper.
TL;DR: The main objective of the paper is to show how the application of goal programming could be of assistance to the educational administrators in the country with respect to determining how to allocate the available resources among the different subsystems of the educational system.
Abstract: There are several factors which account for the inefficiencies observed in the educational system of a less developed country. Some of these factors, with particular reference to the educational system of Greece, are briefly mentioned in this paper. However, the main objective of the paper is to show how the application of goal programming could be of assistance to the educational administrators in the country with respect to determining: (1) how to allocate the available resources among the different subsystems of the educational system and among the different components within each subsystem; (2) the quality level of education that the country can afford; and (3) the financial sacrifices necessary for different levels of improvement.