Application of fuzzy goal programming technique to land use planning in agricultural system

This paper presents how fuzzy goal programming can be efficiently used for modelling and solving land-use planning problems in agricultural systems for optimal production of several seasonal crops in a planning year. In the model formulation of the problem, utilization of total cultivable land, supply of productive resources, aspiration levels of various production of crops as well as the total expected profit from the farm are fuzzily described. In the decision-making situation, minimization of the under-deviational variables of the membership goals with highest membership value (unity) as their achievement levels defined for the membership functions of the fuzzy goals of the problem on the basis of the priorities of importance of achieving the aspired levels of the fuzzy goals to the extent possible is considered. As a study region, the District Nadia, West Bengal, India is taken into account. To expound the potential use of the approach, the model solution is compared with the existing cropping plan of the District as well as a solution of the problem obtained by using the additive fuzzy goal programming model studied by Tiwari et al. (Fuzzy sets and systems 24(1987)27.) previously.     

Goal directed benchmarking for organizational efficiency

In this paper, we extend the standard data envelopment analysis (DEA) model to include longer term top management goals. This extension is in recognition of the fact that benchmarking for decision making units (DMUs) is more than a purely monitoring process, and includes a component of future planning. The new model uses a goal programming structure to find points on the efficient frontier which are realistically achievable by DMUs, but at the same time achieving a closer approach to long term organizational goals (as distinct from the local performance of individual DMUs). Consideration is given to the possibility of adjusting constraints on the DMU by investment in extended inputs or new technologies, in which case minimization of associated investment costs becomes an additional management objective.     

Governmental planning and budgeting with multiple objective models

This paper presents a goal programming model development and application for a state level public health care agency. Only limited applications of macro planning processes related to health care have been presented in the literature. In that regard, this paper describes briefly the goal programming model, the background of the agency involved and the specific models developed. Three formulations of the model are presented involving (1) the resources required to achieve all goals, (2) the goal attainment status utilizing a likely budget and (3) a proposal for resolving the goal desire-resource limitation dilemma.     

University planning: An organization model

As the author points out, University plannign is at a fairly primitive stage of development. The University shares with other non-profit making institutions the problem of defining specific goals of measuring performance towards these goals. He analyses the difficulties of planning in the university environment and to suggest four stages of organization through which universities are likely to pass in developing planning systems.     

Strategic planning in a changing corporate environment

Strategic planning is about nothing, if it is not about attempting to achieve desirable futures. In the past this has often been seen as an excuse, or indeed a necessity, for fixed goals which are constantly timed. Such a state of planning has, fortunately, for a long time now been discredited and this paper concentrates upon the concepts of strategic planning within the changing corporate environment, an environment which therefore has to effect both the goals as well as the process of planning. Furthermore, the author concentrates upon the concept of a planning, allocating, and monitoring cycle of strategic planning which sets the strategic planning concept within a process cycle as well as within an effective allocative structure. The author considers this latter point an extremely important one since, as he says, ‘planning can become a very sterile and barren activity if it is not viewed integrally with acting and doing’. Finally, this paper concentrates on the important fact that planning must, within a dynamic environment, be an iterative and a learning process.     

Manpower planning and individual goals

Manpower planning is often considered as a subsystem within industrial organizations, containing a hierarchy of levels. In this article it is suggested that manpower planning has to reconcile the organization's profitability and employees' individual needs and goals. An attempt is made to analyse some recent manpower planning studies with special regard to the consideration of individual goals and their treatment. In conclusion, the authors propose an approach to considering individual needs and goals in manpower planning systems.     

Matrix games with fuzzy goals and fuzzy payoffs

A two person zero sum matrix game with fuzzy goals and fuzzy payoffs is considered and its solution is conceptualized using a suitable defuzzification function. Also, it is proved that such a game is equivalent to a primal–dual pair of certain fuzzy linear programming problems in which both goals as well as parameters are fuzzy.     

分布式供应链中基于准时制的原油采购计划方法

本文研究了分布式供应链多供应商/多炼油厂的原油采购计划问题,建立了在有限资源约束下的准时制多目标采购优化数学模型,以实现总采购费用和供应链循环时间最小。然后,本文将非线性规划模型转化为线性规划模型,并利用层次分析法(Analytic Hierarchy Process,AHP)与多目标规划相结合的方法求解模型得到采购计划方案。数值仿真结果表明本文所提出的原油采购方法的有效性和实用性。     

Models and methods for workforce planning under uncertainty: Optimizing U.S. Army cyber branch readiness and manning

This work examines the problem of optimally resourcing personnel for a new set of U.S. Army cyber-specialty career fields using a combination of personnel accessions and inter-career-field transfers that are limited to occur over a subset of periods early within a 30-year career cycle. This workforce planning problem is bounded by constraints respectively pertaining to organizational needs for personnel, as well as personnel promotion policies. Complicating the problem are stochastic retention rates for every combination of year and promotion level within each career field over the 30-year period. Upon formalizing this Cyber Workforce Planning Problem (CWPP) within the framework of multiple performance goals, this study formulates, tests, and compares three frameworks to seek optimal workforce planning decisions under uncertainty: two stochastic programming (SP) variants and a robust optimization (RO) representation. Upon sampling the stochastic parametric distributions to generate a set of collectively representative, deterministic scenarios, the SP variants respectively leverage a scenario-based Monte Carlo approach and sample average approximation, whereas the RO model examines robust solutions over a range of decision-maker risk attitudes. A sensitivity analysis applied to the first of the SP variants indicates the solutions are relatively insensitive to different prioritizations of goals, and identifies policy insights to help recruit and retain personnel. Comparative testing of the three methodologies yields workforce planning recommendations that are relatively consistent across solution methodologies and identify concerns to inform changes to personnel policies.     

ON FUZZY GOAL PROGRAMMING*

This paper illustrates how the goal programming problem with fuzzy goals having linear membership functions may be formulated as a single goal programming problem. Also, a previously defined method for dealing with fuzzy weights for each of the goals is re-examined.     

A goal programming model for paper recycling system

The conflict between economic optimization and environmental protection has received wide attention in recent research programs for waste management system planning. This has also resulted in a set of new waste management goals in reverse logistics system planning. The purpose of this analysis is to formulate a mixed integer goal programming (MIGP) model to assist in proper management of the paper recycling logistics system. The model studies the inter-relationship between multiple objectives (with changing priorities) of a recycled paper distribution network. The objectives considered are reduction in reverse logistics cost; product quality improvement through increased segregation at the source; and environmental benefits through increased wastepaper recovery. The proposed model also assists in determining the facility location, route and flow of different varieties of recyclable wastepaper in the multi-item, multi-echelon and multi-facility decision making framework. The use of the model has been illustrated through a problem of paper recycling in India.     

Multiobjective investment planning under uncertainty

In this paper we consider the relevance of various planning methods and decision criteria to multiobjective investment planning under uncertainty. Assuming that a natural reaction to uncertainty is to operate so as to leave open as many good options as possible (as opposed to maximizing subjective expected utility) we argue that the planning process should concentrate on analyzing the effects of the initial decision, and that for this exercise the classical methods of mixed integer programming are inappropriate. We demonstrate how the technique of dynamic programming can be extended to take account of multiple objectives and use dynamic programming as a framework in which we analyze the robustness of an initial decision in the face of various types of uncertainty. In so doing we also analyze the risks involved in both the planning and decision making functions.     

Goal programming and constrained regression—A comment

Goal programming was originated to obtain “constrained regression” estimates for an executive compensation formula which would conform to an organization hierarchy and other company policies prescribed by management. A subsequent history in that context is traced through other uses in personnel planning and in organization designs. Applications to planning advertising strategies are also examined which extend to uses of goal programming that involve fitting frequency functions under a variety of constraints. Finally this is all related to the initial and continuing research on the statistical properties of these estimates.     

Financial planning using goal programming

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.     

ON FUZZY GOAL PROGRAMMING—SOME COMMENTS

This paper pertains to goal programming with fuzzy goals and fuzzy priorities. Hannan [1], in his paper on fuzzy goal programming, alludes to the difficulty of handling fuzzy priorities and further notes that a method that this author proposed [2] may lead to incorrect results. In this note, the general problem of goal programming with fuzzy priorities is reexamined, along with the solution to the specific example presented in my original paper [2]. It is shown that the method for handling fuzzy priorities originally proposed by this author does indeed capture the relative importance of goals.     

The current practice of bank long-range planning

This paper reports on a recent survey of long-range planning practices in 105 large United States banks. The survey results indicate that long range planning is a relatively new corporate activity with more than half the respondents initiating long range planning the last 5 years. To the extent these banks lead others, this finding suggests greater adoption of long range planning systems in small and medium size banks in the future. Profitability and growth goals are the primary goals quantified in the planning process. These goals are pursued via various strategies. Profit goals are typically pursued by improving pricing policies, adjusting mix and maturity of assets and liabilities to minimize adverse effects of interest rate fluctuations, managing spreads through proper loan pricing and bond portfolio management and tightening cost control with a particular emphasis on non-interest expense. Growth goals are achieved by branch expansion, use of bank holding companies, and increased market penetration through product diversification and sales training programmes designed to develop new business. In addition, information is presented on trends that appear to be developing in the area of long-range planning in the banking industry.     

An accounting control system structured on multiple objective planning models

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.     

Elements of effective corporate planning

This paper focuses on several specific areas in corporate planning which heretofore have received limited attention in the literature. These areas include perception of a need for planning, analysis of planning from a process viewpoint with particular emphasis on organizational structure, and elements of effective planning. Data on which conclusions are based were developed through structured in-depth interviews with key planning executives of 14 large corporations in the Pittsburgh Metropolitan area.The study determined that the most prevalent event associated with perception of a need for more formalized planning was a change in top management. The emphasis on planning usually arose from three sets of factors—organizational, external, and performance. The typical planning process involves establishing corporate goals and objectives, setting environmental premises, collecting information and forecasting, establishing divisional goals and objectives, developing divisional plans, and revising objectives and plans if objectives are not met. The major participants in the planning process are top management, the corporate planning department, divisional general management, divisional staff groups, and intermediary planning groups.The study identified necessary conditions for effective planning which included planning knowledge and skills, planning climate, psychological commitment, and effective group behavior. The study also includes a discussion of planning weaknesses, current trends, and recommendations.     

Linking Product Planning and Process Design Decisions

Manufacturing strategy reflects the goals of the business strategy and directs the manufacturing function in achieving them. In this study, we focus on two decision areas with crucial implications for manufacturing strategy: product planning and process design. Using mathematical programming models as a research tool, we test several conjectures in the manufacturing strategy literature regarding linkages between the two decisions. Our results show that a close integration between these decisions helps control the product offerings, stabilize process requirements, improve process technology choices, and increase net cash flows over time. Using the concept of environmental clusters, we found that a close linkage is more critical when the environment is more complex, less uncertain, and tighter. Based on these findings, we present some managerial implications and suggestions for future research.     

SMART oder MOTTO? Von der Hemmung in die Handlungsfähigkeit durch passende Zielformulierung

In consultancies, goals are often set very concrete on a behavioral level which can increase one’s probability of success to attain the goal. However, if people are anxious and worried when they talk about their goals, there seems to be too little identification with the goals and attainment is impossible. The reason is often a conflict between conscious and unconscious needs. The Zürcher Ressourcen Modell (ZRM) has developed MOTTO-goals which are defined on an attitudinal level and bring into accordance consciousness and unconsciousness. They build identification with goals and thus, support goal pursuit. If people already identify with their goals, they can immediately start with concrete planning.