Showing papers on "Goal programming published in 1993"
Book•
01 Jan 1993
TL;DR: Fuzzy Linear Programming.
Abstract: Introduction. Fundamentals of Fuzzy Set Theory. Fuzzy Linear Programming. Fuzzy Nonlinear Programming. Interactive Multiobjective Linear Programming with Fuzzy Parameters. Interactive Multiobjective Nonlinear Programming with Fuzzy Parameters. Interactive Computer Programs. Some Applications. Further Research Directions. Index.
153 citations
TL;DR: In this paper, an effective approach based on the transient energy function (TEF) method of power system transient stability analysis is proposed for stability-constrained rescheduling of the generation and critical line flows for a given initial operating condition and designated contingency.
Abstract: An effective approach, based on the transient energy function (TEF) method of power system transient stability analysis, is proposed for stability-constrained rescheduling of the generation and critical line flows for a given initial operating condition and designated contingency. The sensitivities of the energy margin with respect to changes in generation are used in the transient stability constraints, and distribution factors are used to monitor and constrain the critical line flows. The problem is formulated as a multiobjective optimization problem, which is solved using a goal programming algorithm that incorporates an explicit knowledge base. The approach has been successfully tested on two power systems: a 17-generator and a 50-generator test network. >
99 citations
TL;DR: An efficient algorithm for solving large-scale 0–1 GP problem is proposed, introducing the fuzziness due to judgement of goal accomplishments, with the generalized upper bound structure.
65 citations
TL;DR: In this article, three MCDM techniques: goal programming, multi-objective programming (MOP) and compromise programming (CP) are discussed in terms of their usefulness for practical farm planning.
52 citations
TL;DR: In this paper, the Stochastic Allocative Data Envelopment Analysis (SADEA) model is used to measure relative efficiency for a group of similar operating units with known input prices.
49 citations
TL;DR: In this paper, a non-preemptive goal programming model for the optimal allocation of energy resources to various energy end uses is presented for bridging the energy supply and demand gap in India.
Abstract: The optimal allocation of energy resources to various energy end uses is an important strategy for bridging the energy supply and demand gap in India. It has been recognized that the allocation should be guided by multiple criteria. A multiobjective programming model for such an allocation process is presented in the paper. The normative model has been applied for the households sector of Madras city. The model is solved using non pre-emptive goal programming. Variations in the original model have been made to build alternative scenarios. The results of the original model and the alternative scenarios indicate that the use of solar thermal energy, natural gas, LPG, fuelwood, kerosene and lignite should be promoted for cooking, and the use of grid electricity and diesel, should be promoted for meeting water pumping demands. They favour the use of electricity generated from diesel for lighting, and the use of solar photovoltaics for meeting the electricity demands of household appliances. The results also indicate that grid electricity and electricity generated from fuelwood should be promoted to meet the demands of all the four household end uses, and point to the need for more research into solar photovoltaics, which may become competitive for meeting household demands in the future.
46 citations
TL;DR: Four major approaches of Nonlinear Goal Programming are reviewed and discussed; 1. simplex based; 2. direct search; 3. gradient search and 4. interactive approaches.
37 citations
TL;DR: This paper shows that solutions obtained by this approach are always efficient solutions and is based on the principle of optimality in dynamic programming and fuzzy decision approach.
33 citations
28 Mar 1993
TL;DR: In this article, a parametric generalized goal function is given that unifies many of the commonly used averaging operators for equally weighted objectives and conditions are defined that a generalized weighted goal function should satisfy.
Abstract: In multiobjective fuzzy decision making, averaging operators are commonly used as goal functions. It is assumed that such a goal function attains the maximum value for the optimal alternative. A parametric generalized goal function is given that unifies many of the commonly used averaging operators for equally weighted objectives. The parameters can be interpreted as an indication of the decision maker's optimism. Conditions are defined that a generalized weighted goal function should satisfy. A correct generalization of the goal function for unequally weighted objects is given. >
32 citations
TL;DR: In this paper, the authors present a mathematical model which reflects the three important characteristics of the problem which are: multiple objectives, stochastic inflows, and large-scale nature of the system.
28 citations
TL;DR: In this paper, the authors compare two approaches to the solution of weighted multiobjective linear programming problems: the fuzzy linear programming method and the minmax distance metric, and illustrate the graphical meaning of the weights and the implications to the decision maker.
Abstract: This paper compares two approaches to the solution of weighted multiobjective linear programming problems: the fuzzy linear programming method and the minmax distance metric. The two models produce an identical solution for equally weighted objectives, but the solutions differ when the objectives are unequally weighted. This is due to the underlying meaning of the weights attached to each solution method. The paper illustrates the graphical meaning of the weights and the implications to the decision maker.
Book•
16 Feb 1993
TL;DR: This second edition of linear programming is presented from a very elementary point of view, using as a foundation just a basic knowledge of high school algebra, and helps the reader understand even some of the most subtle aspects of the subject.
Abstract: Linear programming is an extremely useful area of applied mathematics and is used on a daily basis by many industries. Most books on linear programming require an in depth knowledge of linear algebra in their exposition, making the subject matter inaccessible to the average reader. This second edition continues the presentation of the subject from a very elementary point of view, using as a foundation just a basic knowledge of high school algebra. The author manages to go into great depth with these minimal prerequisites, and helps the reader understand even some of the most subtle aspects of the subject. This is accomplished by weaving some of the more difficult ideas into informal proofs, with the result that the reader often doesn't even know he or she is reading very difficult material. Some formal proofs are included, and even these are often broken down into small steps to give them clarity. The reader who gets through the whole book will have a strong knowledge of linear programming and also a good basic knowledge of the related areas of game theory, integer programming, goal programming, network analysis, and dynamic programming. This book can be (and has been) used as a primary text for a course in linear programming and related topics. It can also be used for self study by the person who wants to know more about this fascinating and very useful subject. Exercises have been carefully chosen to illustrate a broad range of applications that occur in practice leaving the reader with an appreciation of the wide applicability of this subject to real life problems. Also, solutions to many of the exercises are given, making this an ideal book for the person who is studying this subject independently.
01 Apr 1993
TL;DR: The Army's enlisted personnel decision support system combines a variety of modeling techniques, such as goal programming, network models, linear programming, and Markov-type inventory projection, with a management information system to support analysis of personnel planning issues.
Abstract: The Army's enlisted personnel decision support system combines a variety of modeling techniques, such as goal programming, network models, linear programming, and Markov-type inventory projection, with a management information system to support analysis of personnel planning issues. Using a hierarchy of models, personnel planning decisions are coordinated from the macroscopic, public policy level to the very detailed, unit and military occupational specialty level. This decision support system employs models that combine the full range of modeling methodologies with mechanisms to assure integration between organizational levels.
Journal Article•
TL;DR: Discriminant analysis, logistic regression, and linear goal programming are alternative techniques used to determine the criterion weights of objects based upon the weighted sum of the criterion scores of each object.
01 Jan 1993
TL;DR: In this article, a dependent-chance goal programming (DCGP) and successive factoring method was used to solve the problem of water supply and allocation in Qinhuangdao region.
Abstract: This paper presents a dependent-chance goal programming (DCGP) and gives a successive factoring method to solve DCGP. We also discuss the application of DCGP in Qinhuangdao region for water supply and allocation.
TL;DR: Warranty cost estimation for multiple products is considered in this paper, where decision variables include the price, warranty time, production quantity, and lot size system constraints on the above decision variables are based on absolute minimum and maximum values between which those variables should lie Several goals are considered at different levels of priorities Some of these goals may be conflicting
Abstract: Warranty cost estimation for multiple products is considered The decision variables include the price, warranty time, production quantity, and lot size System constraints on the above decision variables are based on absolute minimum and maximum values between which those variables should lie Several goals are considered at different levels of priorities Some of these goals may be conflicting The goals considered included operation within a limited resource capacity, the achievement of a specified market share for each product, limitation on the total warranty cost as a given proportion of total sales, limitation of the warranty reserve for a given product as a proportion of the total warranty reserve for all products, and attainment of a minimum level of warranty reserve for a given product as a proportion of the total warranty reserve cost A goal programming approach is used to solve the formulated problem An example is illustrated using the proposed formulation, and goal achievements are discussed Sensitivity analysis is also conducted for some of the model parameters >
TL;DR: An LGP model is developed for allocating an investor's total wealth including nonmarketable assets and demonstration of the informational efficiency of the modeling approach in portfolio analysis is presented.
TL;DR: The development of a multiple objective programming model, using the lexicographic goal programming technique, to help resolve the conflict over water abstraction from the Rakaia River in Central Canterbury, New Zealand is described.
TL;DR: A fundamental ISGP assumption concerning the preemptive relative importance of achieving adjusted goal target levels is shown to be unnecessarily restrictive and is relaxed.
TL;DR: A new formulation of dynamic programming approach to FGCP is proposed here as Dynamic Fuzzy Goal Control Problem (DFGCP) and the method of finding its solution is illustrated with an example.
TL;DR: This research develops a workload balancing model that incorporates a preference list for a fixed number of ambulance stations and simple concepts of queuing theory into a mathematical programming formulation that is able to minimize the workload imbalance among existing stations.
Abstract: This research develops a workload balancing model that incorporates a preference list for a fixed number of ambulance stations and simple concepts of queuing theory into a mathematical programming formulation. The workload balancing model is demonstrated on actual operating data from the Emergency Medical Service (EMS) system of Shanghai, P.R. China. Results indicate that the model is able to minimize the workload imbalance among existing stations by assigning ambulance units on the basis of demand received by each station.
TL;DR: In this paper, a variable goal programming model for mine planning optimization for multi-objective decision-making was developed and applied to a large surface coal mine, where multiple objectives are comprehensively considered according to their different priorities.
Abstract: Goal Programming can be effectively applied to mine planning optimization for multi—objective decision—making. Multiple objectives are comprehensively considered according to their different priorities. A (0,1) variable goal programming model for mid or short term open pit planning has been developed and applied to a large surface coal mine.
01 Sep 1993
TL;DR: A mathematical model is developed for allocating pre engineering students to available majors at an engineering college that considers departments' capacities and students' preferences and gives priority to students with higher Grade points averages.
Abstract: In this paper a mathematical model is developed for allocating pre engineering students to available majors at an engineering college. The model considers departments' capacities and students' preferences. Moreover, it gives priority to students with higher Grade Points Averages (GPA). The model is formulated as a goal programming problem. Its applicability is tested using real data. The model performed significantly better than the manual method presently at use.
TL;DR: A linear goal programming approach with the ability to capture the non-monotonicity of some attribute scores in classification problems is proposed and classification performances of this approach and other classification approaches are evaluated.
TL;DR: A preemptive goal programming model for optimal allocation of personnel time among various tasks in a hospital pharmacy is presented and a recommendation regarding its staffing requirements is made.
TL;DR: The interactive concept provides a learning process about the system, whereby the decision maker can learn to recognize good solutions, the relative importance of factors in the system and then, design a high-productivity system, instead of optimizing a given system.
TL;DR: This paper will propose efficient optimization techniques: a job-control program manages each analysis program linked with another program by data files; each program outputs sensitivity data to construct a linear model of the total system; and a sequential goal programming (GP) formulation is used for multiple-objective design problems.
TL;DR: The problem of flow balance in a long-haul computer communications network is investigated by means of a goal programming methodology which aims at optimizing the received and end-to-end throughput while keeping the total operational cost within reasonable limits.