Showing papers on "Goal programming published in 1983"
TL;DR: The possibility of the identification of a complete fuzzy decision in fuzzy linear programming by use of the parametric programming technique is presented and it is shown that this fact can be useful in the Zimmermann approach to multiple objective linear programming.
406 citations
TL;DR: This paper introduces the approach to generalized goal programming, describes its underlying philosophy, and indicates the specific subclass of models and methods which serve to comprise the overall approach.
147 citations
TL;DR: A branch and bound algorithm is presented which is based on the extension of implicit enumeration techniques to multiobjective zero-one linear programming and which appears to be computationally quite efficient.
Abstract: A branch and bound algorithm is presented which is based on the extension of implicit enumeration techniques to multiobjective zero-one linear programming and which appears to be computationally quite efficient. Domination tests, aiming at identifying paths of the enumeration tree that lead to dominated solutions as high up the tree as possible, are developed. Some computational results are also given.
80 citations
TL;DR: In this paper, the necessary conditions of Fritz John and Kuhn-Tucker type for Pareto optimality are derived by first reducing a vector minimization problem (multiobjective programming) to a system of scalar minimization problems and then using known results in convex programming.
Abstract: Necessary conditions of Fritz John and Kuhn-Tucker type for Pareto optimality are derived by first reducing a vector minimization problem (multiobjective programming) to a system of scalar minimization problems and then using known results in convex programming.
79 citations
TL;DR: Goal programming is presented as a method of achieving nutritional balance in selected diets by demonstrating the goal programming approach and a report of an application of the technique to the selection from 150 food raw materials to satisfy the daily nutritional requirements of Thais.
Abstract: The use of linear programming to select diets to meet specific nutritional requirements frequently results in an over-supply of certain nutrients. Nutritional balance is difficult to achieve in diets selected by linear programming owing to the complex inter-relationships of the constraints. Goal programming is presented as a method of achieving nutritional balance in selected diets. An example demonstrating the goal programming approach is followed by a report of an application of the technique to the selection from 150 food raw materials to satisfy the daily nutritional requirements of Thais. The nutritional balance of the raw materials selected by goal programming showed a marked improvement over that selected by linear programming.
75 citations
TL;DR: In this paper, a branch-and-bound algorithm is developed which can solve the assembly line balance problem for an optimum solution, based on interviews and surveys of practicing engineers, which is the basis for a model in goal programming form.
62 citations
TL;DR: A generalized goal programming model is used to resolve a real-world human resource allocation problem involving allocating teachers to 22 private schools in St. Louis, Missouri and provides a solution that balances cost minimization with preference goals of the teachers, administrators, and schools.
Abstract: A generalized goal programming model is used to resolve a real-world human resource allocation problem involving allocating teachers to 22 private schools in St. Louis, Missouri. The model provides a solution that balances cost minimization with preference goals of the teachers, administrators, and schools.
49 citations
TL;DR: In this article, the authors used goal programming to aid in the selection of rural road projects in the Indonesian Rural Works Program (RWP) in order to analyze the effects of the spatial distribution of investments.
Abstract: The development planner must often face complex problems with multiple, conflicting objectives. Goal programming provides a general methodology for solving such problems. The tool is applied here to aid in the selection of rural road projects in the Indonesian Rural Works Program. Selection criteria are formalized into a set of nineteen goals which form the basis for a goal programming model. Changes in priority levels of goals and weights are used to analyze the respective effects upon the spatial distribution of investments. The approach is applicable to a wide range of problems and a variety of sensitivity analyses. Despite clear advantages, several drawbacks must be noted. First, the application of the methodology, given its degree of sophistication, is limited to a central decision making unit which has access to appropriate software. Second, the technique assumes that the planner has the ability to formulate alternative actions and consequences in a quantifiable expression.
42 citations
TL;DR: Various approaches to implementing the plans evaluation steps of the SIRO-PLAN land-use planning method are described, including linear and goal programming and the LUPLAN simplification of the linear programming approach.
Abstract: In this paper are described various approaches to implementing the plans evaluation steps of the SIRO-PLAN land-use planning method, including linear and goal programming and the LUPLAN simplificat...
40 citations
01 Dec 1983
TL;DR: In this paper, the optimal allocation of data points for regionalized variables is investigated in a nonlinear programming setting, based on the theory of kriging and the properties of the estimation variances.
Abstract: In this paper mathematical programming models and special solution algorithms are presented for the optimal allocation of data points for regionalized variables. Two models are discussed; the first one minimizes the estimation variance subject to a given number of additional measurement points or additional measurement cost. The second model minimizes the number of additional points or additional cost subject to upper bounds given to the estimation variances. The models are based on the theory of kriging and the properties of the estimation variances, which lead to certain multiobject programming problems. As it can be shown, a special branch and bound algorithm can be used for solving the resulting nonlinear programming problems
34 citations
Book•
03 Aug 1983
TL;DR: Information is provided on how to construct models for linear and nonlinear programming using the Simplex Method, as well as some of the techniques used in Integer Programming and Dynamic Programming.
Abstract: LINEAR PROGRAMMING. An Introduction to Linear Programming. The Simplex Method. Duality Theory and Sensitivity Analysis. The Transportation and Assignment Problems. Goal Programming. MATHEMATICAL PROGRAMMING. Network Models. PERT/CPM Models. Integer Programming. Nonlinear Programming. Dynamic Programming. Game Theory. PROBABLE PROBABILISTIC MODELS. Waiting Line Models. Markov Processes. Inventory Models. Simulation Models. Decision Analysis. SYNTHESIS. Implementation of Management Science. Appendices. Answers to Even Numbered Questions. Index.
TL;DR: Results are presented which indicate that diets which are more nutritionally complete can be calculated in less time using this approach than through the classical manual methods.
TL;DR: A new interactive goal-programming method is presented in which the constrained multiple-objectives problem is converted into a sequence of unconstrained single-objective problems and it is shown that under suitable conditions the method converges to a Pareto-optimum.
TL;DR: The Accession Supply Costing and Requirements Model ASCAR as mentioned in this paper uses goal programming to evaluate the accession needs of the All Volunteer Armed Forces to reach or maintain a given strength and optimize the qualitative mix of new recruits.
Abstract: The Accession Supply Costing and Requirements Model ASCAR uses goal programming to evaluate the accession needs of the All Volunteer Armed Forces to reach or maintain a given strength and optimize the qualitative mix of new recruits. The model has been used extensively by the Congressional Budget Office and the Office of the Assistant Secretary of Defense to evaluate the All Volunteer Force, develop recruiting goals, and evaluate retention for all services.
TL;DR: A 0–1 goal programming model is presented, based on an actual case example, for assigning projects to engineers in order to prevent project splitting and excessive manpower requirements, complete as many preferred projects as possible and maximize profits while keeping a balanced workload.
01 Sep 1983
TL;DR: Several ways in which imprecision may be incorporated into the programs are discussed, including proximate programming, inexact programming and fuzzy programming.
Abstract: Conventional linear programming requires the deterministic specification of all the relevant data but generally this is only known imprecisely. Several ways in which imprecision may be incorporated into the programs are discussed. These include proximate programming, inexact programming and fuzzy programming. A simple illustrative example concerned with water quality is reworked using some of the described techniques. Fuzzy programming is a particularly useful model which can handle imprecision with respect to all the parameters and can also incorporate multiple goals.
01 Apr 1983-International Journal of Human-computer Studies \/ International Journal of Man-machine Studies
TL;DR: This work has implemented a module that can act as a decision-support for a variety of expert systems in need of estimates of hidden variable values at any desired time, based on generalized production rules expressing stochastic, causal relations between open and hidden variables.
Abstract: In the area of strategie decision-making, the objective often is to achieve one's own goals and to prevent the achievement of the adversaries' goal. To do so, the decision-maker needs to know, as precisely as possible, the values of the relevant variables at various times. Some of these variables, the open variables, are readily measurable at any time. Others, the hidden variables, can be measured only at certain times, either intermittently or periodically. We have implemented a module that can act as a decision-support tooi for a variety of expert systems in need of estimates of hidden variable values at any desired time. The estimation is based on generalized production rules expressing stochastic, causal relations between open and hidden variables. The quality of the estimates improves through a multi-level learning process as both the number and the quality of the rules increase. The modularity of these causal relations make incremental expansion and conflict resolution naturel and easy. Restricting the set and the domain of pattern formation rules to a reasonable size makes the system effective and efficient. Finally, the system can be easily employed for distributed database applications.
TL;DR: A Note on Computational Methods in Lexicographic Linear Goal Programming and its Applications in Operational Research Society.
Abstract: (1983). A Note on Computational Methods in Lexicographic Linear Goal Programming. Journal of the Operational Research Society: Vol. 34, No. 6, pp. 539-542.
TL;DR: Algorithms are presented which allow one to transform the sequential tableau into the multiphase tableau and vice versa and, in doing so, demonstrate the respective mathematical duals and their relationships.
TL;DR: In this paper, a goal programming technique is used to determine the optimum size of an extended octagonal ring for various goal priorities with respect to sensitivity and rigidity, which arc conflicting in nature.
Abstract: Extended octagonal rings are used in metal cutting dynamometers to measure cutting forces and torque. The controllable design variables are the thickness, radius and width of the ring. Normally the objectives of the design are to achieve high sensitivity and high rigidity which arc conflicting in nature. Therefore, both requirements cannot be achieved simultaneously. The goal programming technique is used to determine the optimum size of extended octagonal ring for various goal priorities with respect to sensitivity and rigidity
TL;DR: The present approach uses the idea of preemptive priority levels with an approximate value function at each level to assess directly a quadratic approximation of the multiattribute value functions.
Abstract: Many common decision-making situations require integration of a number of objectives or goals into a single objective function to be optimized. A number of techniques for performing this analysis are presented in the literature. These procedures generally require a tradeoff between realism and tractability. The present approach uses the idea of preemptive priority levels with an approximate value function at each level. An efficient experimental design is used to assess directly a quadratic approximation of the multiattribute value functions. An existing algorithm is then used to solve the resulting problem. This procedure is shown to give good results when compared to both the value-function method and goal programming.
TL;DR: A straightforward approach is presented which combines generalized networks with goal programming so as to achieve a modeling and solution methodology for multiobjective generalized networks that encompasses the solution to weighted integer foal programming as well as lexicographic integer goal programming problems.
TL;DR: A goal programming model is applied to the problem in wage and salary administration of balancing internal concerns for equity against eternal market prices in the design of managerial compensation structures using an ideal point/Tchebycheff metric approach.
TL;DR: This paper is concerned with two fundamental aspects of this paper: the conceptual and technical differences among objectives, goals, and constraints are not clearly established, and the possible effects of setting pessimistic levels of aspiration in a goal-programming problem are not analyzed.
Abstract: In a recent Journal article Barnett, Blake, and McCarl (BBMcC) provide an interesting and welcome application of linear goal programming. Until recently agricultural economists have been slow in the use of this and similar techniques in farm planning. However, we are concerned with two fundamental aspects of this paper. First, the conceptual and technical differences among objectives, goals, and constraints are not clearly established. This creates difficulties of identifying, unambiguously, situations to which techniques of multiple-goal and multiple-objectives should be applied. Second, the possible effects of setting pessimistic levels of aspiration in a goal-programming problem, allowing goals to be satisfied readily, has not been analyzed.
TL;DR: A survey of quadratic programming practices in corporate and economic planning formulations is presented in this article, where a variety of applications of QP are examined, including portfolio selection, monopolists' profit maximization, inequality constrained least-squares estimation, spatial equilibrium analysis, goal programming with Quadratic preferences, and optimal decision rules.
Abstract: One of the shortcomings of linear programming lies in its linearity assumption, primarily in the objective function. This compels us to work with a constant marginal rate of substitution and constant return to scale. However, this assumption is at variance with the economists' preference postulates. This paper presents a survey of quadratic programming practices in corporate and economic planning formulations. It examines a variety of applications of quadratic programming—portfolio selection, monopolists' profit maximization, inequality constrained least-squares estimation, spatial equilibrium analysis, goal programming with quadratic preferences, and optimal decision rules.
TL;DR: In this paper, an application of the goal programming technique is suggested to optimally design a flywheel-like mass rotating at a velocity of 100 radians per second in a fixed position.
Abstract: A mechanical system comprising a journal and two oil-lubricated sleeve bearings is required to support a flywheel-like mass weighing some 2000 1b and rotating at a velocity of 100 radians per second in a fixed position. The design objectives include both high torsional rigidity of the journal and low frictional resistance in the bearings. Increasing the size of the journal will reduce the torsional flexure but. at the same time, will increase the friction loss. Both objectives are conflicting in nature and. therefore, cannot be minimized simultaneously. To take care of such a conflicting situation, an application of the goal programming technique is suggested to optimally design the system.
TL;DR: A model for planning over a domain of continuous actions, with critical points that are represented symbolically as instantaneous discrete events, which represents a plan for 'forcing' the world function to achieve the goal.
Abstract: : This paper concerns the development of a model for planning over a domain of continuous actions. The envisioned world model consists of a set o piecewise defined functions of time, with critical points that are represented symbolically as instantaneous discrete events. The goal is represented as a point through which the world function must thread at some point in time. World functions are transformed by adding events at various points in time which transform the trajectories in the direction of the goal. As events are added, formulas relating the event times are added to the description of the world. The result is a partial order of events which represent a plan for 'forcing' the world function to achieve the goal. (Author)
Abstract: A multiobjective goal programming method is proposed for use in analyzing problems involving a network flow structure which are commonly found in the wastewater and sludge management systems when cost functions are linear. The goals considered are the minimization of: (1) Costs, (2) water quality impact, and (3) land use impact. The model also selects interceptor routes, treatment plants, transport routes and sludge disposal sites, along with flow directions through these facilities under optimal solutions. A hypothetical example problem dealing with regional wastewater management is analyzed to demonstrate the potential usefulness of the method.