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.     

How planning and capital budgeting improve SME performance

This paper focuses on the use of strategic planning among small and medium sized enterprises (SMEs) in the UK manufacturing sector. It analyses the relationship between the intensity of strategic planning, business objectives, perceived performance, changes in the business environment and the use of capital budgeting techniques. Capital budgeting is of particular interest as an area of investigation, and is one which has seldom featured in previous studies of strategic planning behaviour. These issues were investigated via a survey of UK manufacturing SMEs carried out in the winter of 1996/97.

The key results suggest that SMEs incorporate a range of objectives into their strategic planning process, with profit improvement perceived to be the most important objective, followed by sales growth. SMEs engaged in detailed strategic planning are more likely to use formal capital budgeting techniques, including the net present value method, which is consistent with maximising the companys' value. Perceived profitability and success in achieving organisational objectives were positively associated with planning detail, suggesting that strategic planning is a key component improving performance. Planning detail was also associated with a significantly higher level of perceived change in the business environment.     

Planning models for budgeting teaching resources

This paper relates experience in the development of a set of integrated planning models for a school board in a public school system. Three modules were developed. An enrolment projection module utilizes a modified Markov transition matrix (augmented by adaptive exponential smoothing models to forecast flows into the system). A program review module operates in interactive mode as a deterministic simulation to generate alternative budgets in a ‘planning-programming-budgeting’ context. A resource planning module was produced as an optimizing goal programming formulation, but was not found useful to implement for reasons outlined in the paper.     

Axial solutions for multiple objective linear problems. An application to target setting in DEA models with preferences

In this paper we introduce the class of axial solutions for multiple objective optimization problems in contexts in which partial information on preference weights is available. These solutions combine the use of an improvement axis to direct the search of the most preferred result with the concept of efficiency with respect to preference information.     

Informational impediments to the use of capital budgeting models

The primary purpose of this study was to empirically examine whether or not informational impediments impair or alter decision making, with specific focus on capital budgeting decisions. Based on detailed interviews of senior corporate executives, it appears that management information systems (MIS) are less than adequate in providing the information items required to utilize the non-naive methods of capital budgeting. It is therefore suggested that the MIS concept be vastly broadened in regard to such decisions.     

Developing planning models

Mr. Holloway joined the Gulf Oil Corporation in 1939. His previous publications are in the fields of chemical engineering, statistics and computing.He is now the Senior Adviser on Planning Systems and member of Gulf's European Planning Council.The paper presents the author's view that linear programming is an efficient vehicle for long range planning, that it is more comprehensive and when properly structured requires no more computer time than the perhaps more conventional simulation models.Further, that it has the great advantage that the planner himself can control not only the data content of his model, but can also control the way in which the data is treated within the model even to the extent of making drastic matrix changes.     

A heuristic approach to long-haul freight transportation with multiple objective functions

This paper studies a long-haul freight transportation problem stimulated by a real-life application, whose underlying vehicle routing problem is a multi-objective one, where travel time and route cost are to be minimized together with the maximization of a transportation mean sharing index, related to the capability of the transportation system of generating economy scale solutions. In terms of constraints, besides vehicle capacity and time windows, transportation jobs have to obey additional constraints related to mandatory nodes (e.g., logistic platform nearest to the origin or the destination) and forbidden nodes (e.g., logistic platforms not compatible with the operations required). Based on the network definition, routes can be multimodal. To solve this problem, we propose a heuristic algorithm that can be applied in the tactical and the operational planning phase, and present the results of an extensive experimentation.     

Media selection via multiple objective integer programming

Multiple Objective Integer Linear Programming (MOILP) is presented as an aid to media selection. A MOILP analysis approach recognizes the lack of infinite division in media choices and provides the decisionmaker with an efficient set of alternatives. The decisionmaker may then utilize non-quantifiable criteria to make the final media selection or may use the efficient set developed by the MOILP procedure as a screening mechanism. These screened solutions would then be submitted to further analysis to consider interaction effects, non-linearity and so on. The approach is outlined and an illustrative example using somewhat standard data is provided.     

Computer models for corporate planning

This paper presents results of a survey of corporate modelling in 65 U.K. companies. It shows that corporate models were already used in a wide range of industries by 1973 and analyses the characteristics of these models, the uses to which they were put, the background of the model builders, approaches to development of models that were adopted, costs of development, and indications of success or failure. It is, for instance, shown that many corporate models are relatively small and simple, and have been built by accountants, planners and other ultimate users, using special facilities for corporate modelling offered by computer bureaux and consultants.     

Zero-base budgeting—Dealing with conflicting objectives

While Zero-Base Budgeting (ZBB) has received considerable attention in the public sector, virtually all the studies dealing with the system have neglected or given cursory attention to the problem of multiple conflicting objectives. This paper presents a goal programming approach as a systematic means to develop the ZBB process for multiple objectives. This approach allows the administrators to more realistically portray the decision environment as well as their judgment in their budgetary planning models, thus making the budgeting an effective and pragmatic way to implement the planning and decision making process. This study demonstrates a goal programming based ZBB system in the public sector based on real-world data.     

Scenario aggregation in single-resource production planning models with uncertain demand

In this paper we present an application of the scenario aggregation approach proposed by Rockafellar and Wets to a simple standard multi-product multi-period production planning problem with uncertain demand and setup cost modelled by logical zero-one variables. The uncertainty in demand is expressed by a number of demand scenarios. As compared with more traditional approaches that require distributional assumptions and/or estimates of parameters from historical demand data, the scenario approach offers greater flexibility and makes it possible to take subjective information into account. The scenario aggregation principle and the corresponding progressive hedging algorithm offer a theoretically sound basis for generating consistent solutions for production planning models with uncertain demand. Since the production planning problem studied in this paper is of mixed-integer type the original scenario aggregation approach cannot be applied directly. However, since the integer variables in the production planning model are indirectly coupled to the continuous production decisions an alternative method in which only the production quantities are used to couple the different realizations can be used. This paper is a first attempt to perform this form of coupling. We illustrate the ideas on a small example and use this example to demonstrate how the solution can be evaluated in terms of flexibility measures.     

Assessment of aircraft logistics planning models

An assessment of military logistics planning models offers a great deal of information about the modelling state of art. Such tools include both analytic and simulation model types. They can deal with both static and dynamic characteristics of the environment. They require highly detailed data for their operation and can compute over a large number of interacting variables. Unfortunately, these models do not satisfy adequately the requirements of the particular logistics issue for which they were assessed, which is whether such models can be used in early logistics planning for new weapon systems. One difficulty is that such planning must make extensive use of tradeoffs and sensitivity analysis to take account of the flexibility and uncertainties existing at the early stages. Another is that the existent models call for detailed data which is usually not available at that time. Therefore, although the models do fulfill a particular useful planning function, they must be replaced or augmented by a new class of models that will much more closely satisfy the planning need. This new capability requires a serious research effort that will benefit not only the military logistics planners, but also other planners dealing with large capital development programs.     

Aggregate production planning with workforce transferring plan for multiple product types

This paper presents the aggregate production planning for multiple product types where the worker resource can be transferred among the production lines. A mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A real situation of a manufacturing company was selected as a case study. The actual data was used to test and validate the proposed model. The optimal aggregate production plan provides the information on managing the available production capacity together with the useful workforce transferring plan. The obtained solutions were compared to those of another approach where the workers cannot be transferred among the production lines. The total cost is significantly reduced when the workers are allowed to transfer among the production lines.     

An application of multiple objective linear programming to media selection

A multiple objective linear programming (MOLP) method utilizing interval criterion weights is applied to the problem of media selection. Using this technique, it is possible to analyze a problem more explicitly in terms of the several objectives inherent in many media selection situations. In order to illustrate the interval criterion weights approach, a multiple objective hierarchical media selection model is presented and its computer results discussed. In addition to being able to deal more directly with different decision criteria, a distinguishing feature of the mathematical analysis applied here is that its output enables the media-planner to be presented with a small cluster of candidate media schedules (rather than just one). Then, from this list, the media-planner should be in a position to qualitatively make a final choice as a close approximation to his optimal solution.