Goal Programming: the RPMS Network Approach

This paper presents an application of the Resource Planning and Management Systems (RPMS) network approach to the goal programming (GP) problem as an alternative to several other approaches used in the GP process. The RPMS approach to solving the GP problem is illustrated through an example. Sensitivity analysis is also discussed.     

混合模式下U型装配线平衡问题的目标规划求解

装配线平衡对于提高装配效率和降低装配成本都有重要意义。为了满足顾客需求的多样化和减少成本,通常采用混合模式的装配线。本文针对混合模式下U型装配线平衡问题,提出一个目标规划法以求解该问题,量化示例表明所提方法是有效的。     

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.     

An Optimum Multivariate Stratified Sampling Design with Nonresponse: A Lexicographic Goal Programming Approach

In a multivariate stratified sample survey with L strata and p > 1 characteristics, defined on each unit of the population, let the estimation of all the p-population means be of interest. As discussed by Cochran (1977), since the optimum allocation for one characteristic will not in general be optimum for other characteristics some compromise must be reached in a multiple characteristics stratified surveys. Various authors worked out allocations that are based on a compromise criterion. The resulting allocations are optimal for all characteristics in some sense, for example an allocation that minimizes the trace of the variance-covariance matrix of the estimators of the population means or an allocation that minimizes the weighted average of the variances or an allocation that maximizes the total relative efficiency of the estimators as compared to the corresponding individual optimum allocations. In the present paper the problem of optimum allocation in multivariate stratified random sampling in the presence of nonresponse has been formulated as a multiobjective integer nonlinear programming problem and a solution procedure is developed using goal programming technique. Three numerical examples are worked out to illustrate the computational details. A comparison of the proposed method with some well known methods is also carried out to show the practical utility of the proposed method.     

A Critical Comment on Integer Goal Programming

This note is a contribution to the on-going debate about the merits and demerits of goal programming. We concentrate on the special case of integer goal programming. Examples show that the approach is questionable, especially if used in connection with a standard branch-and-bound-based solution technique.     

Goal Programming Approach to a Type of Quality Control Problem

Fixing the levels of inputs and process variables in order to meet a required specification of output is a common quality control problem. However difficulties can arise when the output has a number of characteristics and when each of these characteristics has to satisfy a specification. Such a problem was met in a paper manufacturing factory and the problem was solved using Goal Programming (GP). The method can be applied to other process control problems and this paper gives the GP formulation of the general process control problem. The paper also gives details of the case study from which the method was developed.     

Fractional Minmax Goal Programming: A Unified Approach to Priority Estimation and Preference Analysis in MCDM

A special minmax goal programming model with fractional goals is formulated and then used as the basis for developing two specific MCDM methods: (1) a method to derive priorities for decision elements from pairwise comparison matrices in the AHP framework; (2) a method to assess an additive value function by analysing some preference information expressed over the set of alternatives on a ratio scale. For both methods a common iterative solution procedure is proposed by using a linear programming formulation.     

确定线性规划全部最优解的方法

使用凸多面体的表示定理 ,导出了标准型线性规划最优解的一般表达式 ,并基于单纯形法 ,给出最优解唯一性条件以及当唯一性条件不满足时求出全部最优解的计算步骤 ,同时附有数值例子 .     

A Review of Goal Programming: A Tool for Multiobjective Analysis

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.     

金融危机对石油市场定价机制的影响分析

本文从市场结构性转变的角度,研究了金融危机对石油市场潜在价格机制的冲击和影响。研究采用内生结构性断点检验方法,考察石油市场的结构性改变特征,并采用多因素动态模型(NW OLS)和GARCH模型,分阶段考察了供需基本面和金融市场驱动因素(股票价格、美元汇率、黄金价格和期货市场投机行为)在石油定价机制演变过程中的作用。实证结果表明,在"金融危机"时期(2008:07-2010:04),供需基本面主导了油价变化,石油市场不能很好地对冲股市价格风险。而在危机之前的"泡沫累积"时期(2004:03_2008:07)和"后金融危机"时期(2010:04-2012:03),金融市场因素可以很好地解释油价波动,但作用机制明显不同。     

A Non-linear Multi-criteria Programming Approach for Determining County Emergency Medical Service Ambulance Allocations

In this paper an integer, non-linear mathematical programming model is developed to allocate emergency medical service (EMS) ambulances to sectors within a county in order to meet a government-mandated response-time criterion. However, in addition to the response-time criterion, the model also reflects criteria for budget and work-load, and, since ambulance response is best described within the context of a queueing system, several of the model system constraints are based on queueing formulations adapted to a mathematical programming format. The model is developed and demonstrated within the context of an example of a county encompassing rural, urban and mixed sectors which exhibit different demand and geographic characteristics. The example model is solved using an integer, non-linear goal-programming technique. The solution results provide ambulance allocations to sectors within the county, the probability of an ambulance exceeding a prespecified response time, and the utilization factor for ambulances per sector.     

A Goal Programming model of the reference point method

Real-life decision problems are usually so complex they cannot be modeled with a single objective function, thus creating a need for clear and efficient techniques of handling multiple criteria to support the decision process. The most commonly used technique is Goal Programming. It is clear and appealing, but in the case of multiobjective optimization problems strongly criticized due to its noncompliance with the efficiency (Pareto-optimality) principle. On the other hand, the reference point method, although using similar control parameters as Goal Programming, always generates efficient solutions. In this paper, we show how the reference point method can be modeled within the Goal Programming methodology. It allows us to simplify implementations of the reference point method as well as shows how Goal Programming with relaxation of some traditional assumptions can be extended to a multiobjective optimization technique meeting the efficiency principle.     

A review of Goal Programming and its applications

This paper presents a review of the current literature on the branch of multi-criteria decision modelling known as Goal Programming (GP). The result of our indepth investigations of the two main GP methods, lexicographic and weighted GP together with their distinct application areas is reported. Some guidelines to the scope of GP as an application tool are given and methods of determining which problem areas are best suited to the different GP approaches are proposed. The correlation between the method of assigning weights and priorities and the standard of the results is also ascertained.