Goal Programming and Agricultural Planning

Goal Programming is similar in structure to linear programming, but offers a more flexible approach to planning problems by allowing a number of goals which are not necessarily compatible to be taken into account, simultaneously. The use of linear programming in farm planning is reviewed briefly. Consideration is given to published evidence of the goals of farmers, and ways in which these goals can be represented. A goal programming model of a 600 acre mixed farm is described and evaluated. Advantages and shortcomings of goal programming in relation to linear programming are considered. It is found that goal programming can be used as a means of generating a range of possible solutions to the planning problem.     

Multicriteria Programming for Financial Planning

Multiobjective programming methods would appear to offer a very attractive alternative to conventional single objective LP models for medium term financial planning. However, prior to implementation, many technical and procedural problems need to be solved. This paper presents in case study form some of these problems and discusses possible approaches to their solution.     

干线公路网等级结构优化的目标规划模型及算法

依据制定中长期公路网规划的需要，建立了一个干线公路网等级结构优化的目标规划模型，并给出了算法及算例。     

Goal Programming Models for Assigning Search and Rescue Aircraft to Bases

This paper develops several variations of a goal programming model for optimally allocating a fleet of search and rescue aircraft to a fixed set of available and potentially available bases. In addition, the model determines the number of aircraft of each type from each base (at which that type has been stationed) to assign to the various search locations. The criterion for optimality is to maximize the probability of locating each distress in a specified time. These models are then modified to include fleet planning issues. Solution procedures relating to the models are discussed.     

Planning Urban Recreational Facilities with Integer Goal Programming

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.     

Horizon Valuations for Mathematical Programming in Financial Planning

Using a linear programming model for the financial planning of an organization requires the specification of a horizon date and a valuation of the firm at that date. Given perfect information about future opportunities, an exact valuation procedure should lead to the same optimal solution of the model regardless of the choice of horizon date. Even in the absence of perfect information, conventional valuations fall far shorter of this ideal than they need to. It is shown that for a modest increase in the size of the linear programme, better valuations can be achieved and, most importantly, valuations which consider the impact on the value of the firm of post horizon constraints and liabilities as well as post-horizon opportunities.     

A Markovian Goal Programming Approach to Aggregate Manpower Planning

The combination of a manpower supply model (a Markov type model based on historical probabilities of losses, promotions and gains) and goal programming with preemptive priorities provides a useful tool for developing a future year manpower plan under conflicting socio-econo-organizational objectives. Successful utilization requires a close management involvement in adjusting probabilities and specifying goals, priorities and impending policy changes. Such an approach is presented in this paper and illustrated by means of an industrial case study example. The presentation is kept simple, yet detailed and unified, so that is is easily understood by practitioners and students of operational research/management science.     

A Linear Goal Programming Model for Planning the Exports of Emerging Countries

A linear goal programming model for planning the exports of emerging countries is formulated in this paper. The model includes some economic factors which may affect the exports, e.g. industrial structure, labour force, value added in exports, capital efficiency, imports of raw material used for manufacturing goods designated for exports, investment plan, etc. An illustrative example is presented. A sensitivity analysis was performed in order to examine the effect of various changes made in the model on the results. It is felt that the model presented in this study would be useful to economic planners in emerging countries.     

Diet Planning in the Third World by Linear and Goal Programming

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.     

Goal Programming and Extensions

Journal of the Operational Research Society -     

具有分数形式的随机目标规划在金属模型中的应用

本文主要应用了Enrique Ballestero提出的一个新的随机目标规划框架,采用了幂效用函数和双曲绝对风险厌恶,以资产组合选择问题为背景,构造了两个具有分数形式目标函数的随机目标规划模型,给出了解法,并讨论了解的经济意义。本文的随机目标规划产生了一种相对风险极小的有效解,为决策提供了一种新的方案选择途径。     

A Note on Diet Planning in the Third World by Linear and Goal Programming

This note sets out to counter the view that goal programming applied to diet planning offers little improvement over conventional linear programming techniques.     

Interactive Sequential Goal Programming

This paper introduces a new solution method based on Goal Programming for Multiple Objective Decision Making (MODM) problems. The method, called Interactive Sequential Goal Programming (ISGP), combines and extends the attractive features of both Goal Programming and interactive solution approaches for MODM problems. ISGP is applicable to both linear and non-linear problems. It uses existing single objective optimization techniques and, hence, available computer codes utilizing these techniques can be adapted for use in ISGP. The non-dominance of the "best-compromise" solution is assured. The information required from the decision maker in each iteration is simple. The proposed method is illustrated by solving a nutrition problem.     

An Exact Method for Fractional Goal Programming

Goal Programming with fractional objectives can be reduced to mathematical programming with a linear objective under linear and quadratic constraints, thus optimal solutions can be obtained by using existing Global Optimization techniques. However, only heuristic procedures are suggested in the literature on the field. In this note we explore the practical applicability of a recent algorithm for nonconvex quadratic programming with quadratic constraints for this problem. Encouraging computational experiences for randomly generated instances with up to 14 fractional objectives are presented.     

可拓目标规划方法及其应用

本文基于可拓数学和物元分析理论，介绍了可拓集合、关联函数和可拓满意点等概念，提出了可拓优化的概念，建立了可拓目标规划模型，给出了可拓目标规划方法的算法．实例表明，可拓目标规划方法有一定的实用性．     

Goal Programming in Preference Decomposition

In choosing the best alternative with respect to multiple criteria, one approach is to estimate the criterion weights that influence the preferences of all the alternatives presented. When decision makers are able to make preference judgements based on the alternative as a whole, preference decomposition methods attempt to determine part-worths which represent the contribution of the criterion levels to the overall preference values. For each alternative, the sum of the part-worths estimates its overall preference value. In this work, we use linear goal programming to determine the part-worths of all the criterion levels. Simulation experiments are conducted to compare the performances of linear goal programming and ordinary least squares regression in preference decomposition and to examine the effectiveness of including constraints on the parameters. Our simulated results suggest that the linear goal programming model with constrained parameters has better predictive power.