Showing papers on "Goal programming published in 1980"
104 citations
TL;DR: Methods of implementing the 'what-if' concept are discussed which overcome the problems created by the immense storage requirements and the necessity of assigning the various penalties.
Abstract: Financial planners within industrial organizations are often given the impossible task of formulating a multi-year financial plan which is severely over-constrained. As the planner attempts to meet one objective another variable (or ratio of variables) becomes unacceptable and he is faced with the familiar ‘balloon squeezing’ effect. The problem is one of multiple conflicting objectives (goals) hence lends itself very well to a goal programming method of solution. This approach provides a powerful ‘what-if’ device for the financial planner and allows him to arrive at a satisfactory solution by examining the various trade-offs among the conflicting goals. To be an effective and usable tool, the individual goals are not assigned a priority coefficient as is typical of most goal programming applications. Rather, the planner can reflect his priorities in the manner in which he performs the subsequent what-if analyses. Also, a more flexible penalty function is introduced allowing the planner to assign a more realistic set of penalities which vary in severity over a specified range. Methods of implementing this concept are discussed which overcome the problems created by the immense storage requirements and the necessity of assigning the various penalties.
70 citations
69 citations
57 citations
TL;DR: This study develops a method for the siting of multilevel EMS systems so that each service level maximizes coverage of its own demand population, and “back-up” coordination between levels is assured.
Abstract: Facility siting models known as location covering techniques have proven to be useful particularly for emergency medical services (EMS) planning, given the importance of ambulances responding to demand within some maximum time constraint. These models represent a set of methods which focus the health planner's attention on the access of people to health care, since they attempt to “cover” people in need of service within some specified time standard. This research develops a technique for the locational planning of sophisticated EMS systems, characterized by multiple levels of emergency health services. Specifically, a two-tiered system with “basic life support” and “advanced life support” capabilities is modeled as a goal program. By applying location covering techniques within a goal programming framework, this study develops a method for the siting of multilevel EMS systems so that (1) each service level maximizes coverage of its own demand population, and (2) “back-up” coordination between levels is assured. The usefulness of this goal program as a health planning tool is evidenced in the model's explicit articulation of EMS policy objectives and its ability to link system levels in terms of “goal-directed behavior”. The working of this multilevel covering model is demonstrated by reference to EMS planning scenarios and related numerical examples.
56 citations
TL;DR: Having reviewed a number of modeling approaches, the authors are able to draw certain conclusions as to their applicability for solving various practical problems.
Abstract: To manage its manpower, the organization must be informed about its internal dynamics and about the dynamics of its environment. This involves the monitoring of internal personnel movements and the analysis of external supplies. The internal situation can largely be controlled through hirings, promotions, internal transfers, redundancies and retirement planning. The problem is precisely to plan and control these interrelated activities in order to achieve a stable organization capable of meeting its objectives. The influence of the environment, through the economic situation, legislation, competition and other factors complicates the problem further. To assist in the planning and control of these activities, the organization can have recourse to models that are either descriptive (Markov chains, renewal models) or normative (linear and goal programming, network methods, stochastic programming). Having reviewed a number of modeling approaches the authors are able to draw certain conclusions as to their applicability for solving various practical problems.
56 citations
TL;DR: The class of techniques which do not require prior articulation of preferences and which provide alternative solutions rather than a single optimum is characterized and compared to goal programming.
Abstract: The move toward public decision making based on multiple objective analysis has occurred largely during the past decade. During this brief interval dozens of techniques have been advanced for this purpose. The class of (generating) techniques which do not require prior articulation of preferences and which provide alternative solutions rather than a single optimum is characterized and compared to goal programming. Goal programming, as generally employed, seeks a single optimum solution given an articulated set of targets and priorities on the relevant objectives. Four criteria were used in this comparison and neither approach was found to be unambiguously superior.
47 citations
01 Jan 1980
TL;DR: This paper presents an algorithm that combines the advantage of the flexibility of goal programming with the robustness and the learning character of interactive procedures in an efficient and scalable manner.
Abstract: The paper is devoted to Interactive Multiple Goal Programming (IMGP). This new variant of goal programming tries to combine the advantage of the flexibility of goal programming with the robustness and the learning character of interactive procedures. After a description of the algorithm and some technical details, a numerical example is presented.
46 citations
TL;DR: It is shown how the ordmal priomty factors m the goal programmmg objective function can be used to partmon the goal constraints of the problem, allowing a sequence of smaller subproblems to be solved in order to fred a solution to the original problem.
Abstract: An algorithm Is presented for solving the hnear goal programming problem It is shown how the ordmal priomty factors m the goal programmmg objective function can be used to partmon the goal constraints of the problem, allowing a sequence of smaller subproblems to be solved in order to fred a solution to the original problem. Also discussed is the additional efficiency of the algorithm achieved by the use of variable elnninatmn and special terminatmn rules. Prehminary computatmnal results demonstrate the efficiency of the new algorithm.
45 citations
TL;DR: In this paper, the notion of nondominance in goal programming (GP) is investigated and a test for determining whether an optimal GP solution is GP-nondominated is provided.
Abstract: This paper investigates the notion of nondominance in goal programming (GP). Nondominance in the standard sense of a vector maximum (VM) problem is not always desirable. A definition of “GP-nondominance” and a test for determining whether an optimal GP solution is GP-nondominated are provided. It is demonstrated that one or more GP-nondominated solutions can be found by exploring the alternative optima of the GP solution. A formulation for determining the set of GP-nondominated solutions is provided and examples are used to illustrate the concept of GP nondominance.
45 citations
TL;DR: A goal programming model for planning officer accessions to the U.S. Navy from various commissioning sources is developed and described in this paper, where present and future requirements for different career specialty areas in the Navy are considered in terms of years of commissioned service and related to various "choke points" where inventories fall short of requirements in officer force structure.
Abstract: A goal programming model for planning officer accessions to the U.S. Navy from various commissioning sources is developed and described. Present and future requirements for different career specialty areas in the Navy are considered in terms of years of commissioned service and related to various “choke points” where inventories fall short of requirements in officer force structure. An illustration of the use of this model is provided which involves assessments of the effects of phasing out one comissioning source. Other uses and possible further extensions are also indicated for this model, which now forms a part of the Navy's manpower planning procedures.
TL;DR: An example of the application of nonlinear goal programming in a simple hypothetical transducer design is presented to demonstrate the value of the optimal compromise approach for this or more complex systems.
Abstract: The design of Tonpilz piezoelectric transducers often involves the satisfaction of multiple, conflicting design specifications. To arrive at an optimal compromise solution to a specific design formulation, nonlinear goal programming techniques can be applied. For this optimization technique, a mathematical model of the transducer and its associated housing is constructed and the values of the desired transducer responses and attributes—the design objectives—are computed. The nonlinear goal programming formulation minimizes the differences between the objectives and their specifications. The use of priorities and weights in this minimization process is the key to the great utility of the technique. An example of the application of nonlinear goal programming in a simple hypothetical transducer design is presented to demonstrate the value of the optimal compromise approach for this or more complex systems.
TL;DR: An attempt is made to present the reader with a logical structuring of multiobjective optimization and, in particular, to identify goal programming's place and role within this framework.
TL;DR: This paper shows how the new partitioning algorithm can be extended with a modified branch and bound strategy to solve both pure and mixed type integer goal programming problems.
TL;DR: A lexicographic ordering approach is used to analyse this system of groups, while the solution structure of each individual group is developed using the method of constraints.
TL;DR: Goal programming, a member of the general multiple objective linear programming (MOLP) model, improves upon these among other disadvantages thereby emerging as a more efficient tool for student assignment problems.
Abstract: This paper develops a goal programming model for achieving racial balance in segregated public schools. The model is illustrated and offered as an improvement upon linear programming, a model previously applied in the literature which allows a single objective function only and, in comparison with goal programming, requires more variables and constraints. Goal programming, a member of the general multiple objective linear programming (MOLP) model, improves upon these among other disadvantages thereby emerging as a more efficient tool for student assignment problems.
TL;DR: Goal programming, being a broadly used decision tool, is shown in this paper to be a powerful forecasting device too and GP is intended to relax many of the assumptions of conventional econometric forecasting, which render it inadequate under the prevailing conditions of quickly changing energy structures.
TL;DR: A substantial restudy of the project was undertaken in 1974-76 by the Corps of Engineers as discussed by the authors, which utilized goal programming in order to consider both economic and environmental objectives simultaneously, since these objectives had been considered separately before.
Abstract: A Cross-Florida Navigable Waterway was proposed by the Jefferson Administration (1801–1809) and Congress authorized the first study in 1826. Four alternative routes were considered in the Survey Report of 1829 (Senate Document 102, 20th Congress). Serious construction of the Cross-Florida Barge Canal (CFBC) began in 1964 on the basis of a 1942 authorization. Construction was halted in 1971 with the project about one-third completed and with a sunk investment of about $74 million. Its status is described as “holding.” A substantial restudy of the project was undertaken in 1974–76 by the Corps of Engineers. One of these restudy efforts, sponsored by the Environmental Protection Agency, utilized goal programming in order to consider both economic and environmental objectives simultaneously. Since these objectives had been considered separately before, the approach was a step forward. There were the difficult problems of quantification of environmental goals and specification of priority weights to measure ec...
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01 Jan 1980
TL;DR: In this article, an interactive algorithm for multicriteria decision-making is presented, which is based on multi-objective linear programming (MLP) and subjective programming.
Abstract: "Characterization of Pareto and Lexicographic Optimal Solutions".- "Duality Based Characterizations of Efficient Facets".- "Sensitivity Analysis in Multiple Objective Linear Programming: Changes in the Objective Function Matrix".- "Exhaustible Resources and a Leontief Model of Production with Scarce Energy".- "Multicriteria Decision Models with Specified Goal Levels".- "Multiple Objective Linear Programming and the Tradeoff - Compromise Set".- "A Note on Size Reduction of the Objective Functions Matrix in Vector Maximum Problems".- "The Surrogate Worth Trade-Off (SWT) Method and its Extensions".- "Bicriterion Path Problems".- "The Haar Condition in Vector Optimization".- "A Comparative Evaluation of Conjoint Measurement and Goal Programming as Aids in Decision Making for Marine Environmental Protection".- "An Experiment with Some Algorithms for Multiple Criteria Decision Making".- "How to Order three Hypotheses According to their Plausibility".- "A Bargaining Model for Solving the Multiple Criteria Problem".- "On Computing the Set of all Weakly Efficient Vertices in Multiple Objective Linear Fractional Programming".- "Multiple Goal Operations Management Planning and Decision Making in a Quality Control Department".- "A Multiple Criteria Analysis Model for Academic Policies, Priorities, and Budgetary Constraints".- "Flexibility and Rigidity in Multicriterion Linear Programming".- "Subjective Programming in Multi-Criterion Decision Making".- "Linear Regression Using Multiple-Criteria".- "Interactive Multiple Goal Programming: an Evaluation and Some Results".- "Psychological Factors in Decision Making: New Decision Models".- "Using Preference Information in Multistep Methods for Solving Multiple Criteria Decision Problems".- "Manpower Allocation with Multiple Objectives - The Min Max Approach".- "Multicriteria Decision-Aid-Making in Production-Management Problems".- "The Use of Local-Global Mapping Techniques in Analysing Multi Criteria Decision Making".- "A Satisfying Aggregation of Objectives by Duality".- "Interactive Algorithm for Multiobjective Optimization".- "Ranking of Multiattribute Alternatives with an Application to Coal Power Plant Siting".- "Efficient Stopping of a Random Series of Partially Ordered Points".- "An Interactive Branch and Bound Procedure for Multicriterion Integer Linear Programming".- "The Use of Reference Objectives in Multiobjective Optimization".- "Multiperiod Portfolio Selection and Capital Asset Pricing".- "BehaviorBases and Habitual Domains of Human Decision/ Behavior - Concepts and Applications".- "Methods for Solving Management Problems Involving Multiple Objectives".- Conference Program.- List of Participants.
TL;DR: In this article, integer goal programming combined with simulation is suggested as an alternate approach for solving the dynamic multiple-objective problem, which is otherwise viewed as an excellent attempt at modeling realistic aspects of the portfolio selection problem.
Abstract: In a recent issue of Decision Sciences, Muhlemann, Lockett, and Gear [8] developed a multiple-objective, stochastic linear programming formulation of the multiperiod portfolio selection problem under uncertainty. The purpose of this note is to offer some extensions to their multicriteria approach which is otherwise viewed as an excellent attempt at modeling realistic aspects of the portfolio selection problem. Further, integer goal programming combined with simulation is suggested as an alternate approach for solving the dynamic multiple-objective problem.
TL;DR: In this paper, the authors describe how to set up multiple goal planning models by using goal programming and multiple objective linear programming techniques, and an opportunity cost concept of ex post accounting variance analysis (which a comparison is made between an ex ante budget, ex post optimum budget, and actual results) is used as a control device.
Abstract: An important problem confronting decision makers in modern organizations is how to plan and control in a multiple goal decision setting. The usual approach for attacking this problem is to assume one dominant goal and treat others as constraints for the budget planning purpose. The traditional accounting control system is a variance analysis which makes a comparison between an ex ante planning budget, a budget adjusted to the actual activity level, and actual results. The present paper describes how to set up multiple goal planning models by using goal programming and multiple objective linear programming techniques. And an opportunity cost concept of ex post accounting variance analysis (which a comparison is made between an ex ante budget, ex post optimum budget, and actual results) is used as a control device. This ex post analysis will signal a deviation in any data input parameter in the planning models.
TL;DR: The multiple objectives of perishable product inventory management are examined and a goal programming model for solving redistribution problems is presented and sensitivity analysis is performed to determine when redistribution is advantageous.
TL;DR: In this article, a separable programming (SEP) approach is presented as an improved solution methodology for aggregate production planning, where the LDR cost functions for the paint shop are approximated by piecewise linear segments.
Abstract: Many Production Managers are faced with the problem of planning production, inventory and work force under the constraint of limited resources to meet a seasonal demand. Considerable research has been done on this planning problem and various models have been proposed. The linear decision rule (LDR), especially as applied to the well-known Paint Shop, represents a milestone in the development of such models and serves as a standard against which the performances of many other models are measured. A separable programming (SEP) approach is presented as an improved solution methodology for aggregate production planning. The LDR cost functions for the paint shop are approximated by piecewise linear segments. The results of this model are compared to various other planning models (e.g. linear programming (LP), goal programming and LDR models). In those cases where linearity of the cost functions of an undertaking may reasonably be assumed, an ordinary LP model suffices. In many cases, however, this simple line...
TL;DR: In this article, a goal programming approach for chemical production planning is presented and illustrated by means of an industrial case study example along with implications and extensions of the basic model, which is kept simple so that it is understood by students and practitioners interested in chemical process planning.
Abstract: Production planning in a chemical plant requires determination of production quantities for several intermediate and final products. The production plan must satisfy several absolute requirements (material balances, production capacities, etc.) and conflicting objectives (profits, costs, sales limits, environmental pressures, equipment utilization and other engineering objectives). A goal programming approach for chemical production planning is presented and illustrated by means of an industrial case study example along with implications and extensions of the basic model. The presentation is kept simple so that it is understood by students and practitioners interested in chemical process planning.
TL;DR: In this paper, a multi-objective formulation of a research resource allocation decision for ballistic missile defense technology management is presented. But, the problem of resource allocation is not addressed in this paper.
Abstract: This paper describes a multi-objective formulation of a research resource allocation decision which treats both project selection and funding level considerations. The procedure, which is now being integrated into the planning process for ballistic missile defense technology management, should find many applications in research management activity. We will illustrate the procedure with an actual ballistics missile defense case situation involving six research projects relating to various aspects of strategic defense systems analysis. All descriptive data used in the case is from the 1979 fiscal year.
TL;DR: In this article, the authors discuss the limitations of a model presented by Muhlemann, Lockett, and Gear for the portfolio selection problem in multiple-criteria situations under uncertainty.
Abstract: Harrington and Fischer [2] discuss some of the limitations of a model presented by Muhlemann, Lockett, and Gear [8] for the portfolio selection problem in multiple-criteria situations under uncertainty. They go on to propose integer goal programming and simulation as an alternative solution procedure. The purpose of this note is to critically examine their proposal and to contrast the two approaches. It is shown that the problem is being viewed from different decision-making standpoints.
01 Jan 1980
01 Jan 1980
TL;DR: In this paper, the authors compared the use of two MCDM methods (goal programming in an extended form and direct utility assessment via conjoint measurement) for determining solutions to a resource allocation problem confronted by the U. S. Coast Guard's Marine Environmental Protection Program.
Abstract: This paper compares the use of two MCDM methods — goal programming in an extended form and direct utility assessment via conjoint measurement — for determining solutions to a resource allocation problem confronted by the U. S. Coast Guard’s Marine Environmental Protection Program. The problem is discussed, solutions generated and an analysis is then presented to explain why the goal programming method appears to have been more attractive to Coast Guard decision makers.
TL;DR: This paper used goal programming to evaluate the nature and relative importance of organizational goals, critical constraints affecting the organization and marketing program alternatives, and evaluated the goal attainment potential associated with proposed tourism marketing programs alternatives.
TL;DR: In this paper, the duality theory of linear programming is extended to handle the effects of changes in parameters after the optimal solution has been obtained, and a duality-based sensitivity analysis helps a decision maker have a better feel for the soundness of bis priority structure of goals.
Abstract: Empirical applications of goal programming with pre-emption to-date have failed to deal with the effects of changes in parameters after the optimal solution has been obtained. A few studies that attempted to do this employed the existing linear programming packages as the basic tool for the analysis, with numerical weights assigned in place of the pre-emptive priority factors. Here an attempt is made to extend the duality theory of linear programming and to relate it to the analysis c f po8t-optimality, especially regarding changes in the priority structure. To this end, the dual problem is constructed and interpreted. It is shown that a duality-based sensitivity analysis helps a decision maker have a better feel for the soundness of bis priority structure of goals.