Linear programming techniques in R & D project planning

In a multi-project industrial R & D organization the selection of projects with potentially good payoffs has to be fitted in with the planning of on-going projects as they compete for the same expert staff, laboratory equipment, pilot plant rigs and other facilities and resources. A linear programming approach to this planning problem takes account of any flexibility possible in allocating resources to projects, and in their timing in finding the ‘best’ plan. This is the one which maximises the potential payoff for the whole ‘portfolio’ of projects and makes the most efficient use of the available resources. The principles of the formulation of such LP models and the interpretation of the results produced in terms of practical planning are discussed.     

Risk return approach to product portfolio strategy

This article describes how a risk-return portfolio analysis, as originally developed in economics and finance, can be applied to product-line decisions. This approach uses direct estimates of return, and explicitly considers risk, or variation in return; most of the product portfolio models in use today forecast return by correlation, and lack explicit treatment of risk. The approach provides guidance for new product development activities as well as for allocating resources among a corporation's existing product lines. The article explains how organizations can apply this approach to their own product portfolio decisions, and includes a detailed example of how one company used this model.     

A MILP model for the long term academic staff size and composition planning in public universities

This paper proposes a model for dealing with the long term staff composition planning in public universities. University academic staff is organized in units (or departments) according to their field of expertize. The staff for each unit is distributed in a set of categories, each one characterized by their teaching hours, cost and other specificities. Besides the use for planning (and updating a plan), the model can be used to assess the impact that different strategies may have on the personnel costs and the structure of a university. The proposed model is formulated generally, so it can be applied to different types of universities attending to their characteristics. The model is applied to a real case and validated by means of a computational experiment considering several scenarios. The analysis is focused on achieving a preferable academic staff composition under service level constraints while also minimizing the associated economic expenditures considering a long term horizon. The results show that the model successes in approaching the staff composition to a previously defined pattern preferable one.     

A LINEAR PROGRAMMING MODEL OF RESOURCE ALLOCATION IN A UNIVERSITY*

This paper describes the application of a linear programming model to the process of resource allocation at Illinois State University. The model developed is a general model designed to assist academic administrators in allocating the scarce resources at their disposal. The model, and the assumptions upon which it is based, may be altered to suit the particular decision criteria of any particular academic institution. The linear programming model developed here maximizes an objective function which reflects the total net social profit realized by the university on its outputs to society. This objective function was maximized subject to a myriad of constraints which reflected the limitations of budget, space, and other scarce inputs. Further, the constraints reflect the joint interdependency of many parts of the university and the particular educational delivery system employed by a given department. The outputs of the model include the optimal mixture of academic outputs by the university, the optimal distribution and usage of inputs inside the university, and the shadow price of each input. While the linear programming model developed here is general and may be applied to any university, it was applied to Illinois State University in this paper. In the case of Illinois State University, the model recommended a substantial reduction in emphasis upon teacher education.     

Long range planning for universities

Slower growth in the demand for university places, increasing volatility in the composition of this demand and governmental cut-backs in higher education have created new pressures on university managers. Universities have, however, not adopted long-term strategic planning as a means of handling these problems.

Despite obvious differences of mission and market, the university shares all the problems that business concerns have in adapting to a changing environment. A systematic approach to strategic planning in universities is outlined. The system represents an interesting case study of long range planning for non-profit making service institutions, an expanding sector of today's economy.     

Allocation of seminar applicants

The allocation of seminar applicants is an important issue in educational planning, and each semester a university administration has to deal with this kind of problem. The task here is to reconcile the preferences and priorities of the students, professorships and the university administration itself. This paper shows that if the planning procedure is based on a simple selection strategy, the capacity utilization can be suboptimal; this result is evidenced by a simulation study. To remedy this deficit—and to justify the respective interests—we propose a mixed-integer goal programming approach for assigning students to seminar courses. In addition, we show that this problem can be reformulated into a linear one. All investigations in this paper are illustrated by a real-world application for the University of Hagen, Germany.     

ENROLLMENT FORECASTING: USE OF A MULTIPLE-METHOD MODEL FOR PLANNING AND BUDGETING*

A multiple-method approach is presented for making enrollment projections at the departmental, school, and university level. The various methods utilized are based on the application of a cohort model (macro level) and regression techniques (micro level). The model demonstrates its flexibility in selecting one of a number of regression techniques according to a comparison approach using historical and projected results. This multiple-method approach has proved to be highly accurate and thus useful in allocating and redistributing resources to the operating units of a university. Previous efforts have relied almost solely on a single regression technique for projections and allocation purposes rather than a method based on a measure of flexibility, adaptability, and prediction confirmation.     

ANALYSIS OF A PH.D. PROGRAM VIA GERT MODELING AND SIMULATION

This paper presents a model developed for the planning and control of a Ph.D. program in business administration at a major southeastern university. The technique employed was network simulation (GERT-type) which was selected for its capability to incorporate the stochastic nature of the system into the model. Included in the model are all the sequential steps of the Ph.D. program, such as course work, written preliminary exams, oral exams, dissertation and oral defense, as well as the various probabilistic outcomes and feedback loops of the process. The simulation output yields statistical estimates on program duration and probabilities of various outcomes. The model and simulation results can be used by both university administrators and Ph.D. candidates for planning purposes. The model is flexible in that it can be altered to reflect the unique features of Ph.D. programs of most schools.     

Resource Allocation in Integrated Preoperational and Operational Management of Natural Hazards

The management of natural hazards occurring over a territory entails two main phases: a preoperational —or pre-event—phase, whose objective is to relocate resources closer to sites characterized by the highest hazard, and an operational —during the event—phase, whose objective is to manage in real time the available resources by allocating them to sites where their intervention is needed. Obviously, the two phases are closely related, and demand a unified and integrated treatment. This work presents a unifying framework that integrates various decisional problems arising in the management of different kinds of natural hazards. The proposed approach, which is based on a mathematical programming formulation, can support the decisionmakers in the optimal resource allocation before (preoperational phase) and during (operational phase) an emergency due to natural hazard events. Different alternatives of modeling the resources and the territory are proposed and discussed according to their appropriateness in the preoperational and operational phases. The proposed approach can be applied to the management of any natural hazard and, from an integration perspective, may be particularly useful for risk management in civil protection operations. An application related to the management of wildfire hazard is presented.     

Corporate product planning: A vector analysis approach

This article presents one approach for reviewing corporate product decisions using vector analysis. Vector analysis is a relatively little used technique in business; however, it is helpful in dealing with marketing problems involving more than two major variables. This technique is especially useful to marketing executives since it can provide information for allocating resources to each brand in the product line.The companies in which this technique may be applied share certain characteristics: all have multi-products which are substitutable and distributed nationally; all depend on marketing as an important part of their operations and all use marketing research on a regular basis.     

From knowledge to decision – a case study of sales and operations planning in health care

One of the most important challenges in health care management is balancing resources with fluctuating and uncertain demand. This study examines whether introducing a standardised process for sales and operations planning at a large university hospital improved specialty department managers’ knowledge of planning conditions and if so, whether decisions were made based on this knowledge. Using responses from a survey of 30 specialty department managers at Sahlgrenska University Hospital in Sweden, the analyses indicate that operational knowledge strengthens insights about the needs for strategic decisions, and vice versa. Moreover, knowledge is a necessary, but not sufficient, condition for making decisions at the department level. An overall planning and decision structure is required and should be implemented first at the hospital level to effectively allocate resources.     

DYNAMIC COURSE SCHEDULING FOR COLLEGE FACULTY VIA ZERO-ONE PROGRAMMING*

This paper formulates a multi-period course scheduling problem as a zero-one programming model. Under various constraints, and for a planning horizon of several terms, the model seeks to maximize: (1) the faculty course preferences in assigning faculty members to courses, and (2) the faculty time preferences in allocating courses to time blocks, via a two-stage optimization procedure. The multi-period structure of the model, strengthened by the explicit inclusion of a wide-range of constraints designed to represent various special requirements has enabled the model to capture the many dynamic features of the course scheduling problem at the college level. As such, it can be used not only for long-range or short-range departmental planning, but also as a suitable framework toward the development of a larger, and all-inclusive course scheduling decision system. The paper begins with a brief review of several related studies and then presents a multi-period scheduling model and its extensions. Some numerical examples are used to test the model, and the authors' experience, resulting from such tests with several computer codes, is reported. The possible directions for future research are also suggested.     

EFFECTS OF LEARNING ON RESOURCE ALLOCATION DECISIONS

Learning curves have important implications for managerial planning and control. This paper considers the effect of learning on managerial planning models for productmix problems that can be handled by a linear-programming formulation. An approach to incorporate learning effects in the planning model is proposed in this paper. The feasibility and superiority of the proposed approach over the traditional approach are discussed through the use of a linear-programming problem.     

A GOAL PROGRAMMING MODEL FOR ALLOCATING HUMAN RESOURCES FOR THE GOOD LABORATORY PRACTICE REGULATIONS

The Food and Drug Administration's final Good Laboratory Practice regulation will have a far-reaching effect on testing laboratories that are conducting nonclinical laboratory safety tests. This paper develops a goal programming decision model suitable for setting objectives, meeting budgetary and operational constraints, planning personnel utilization, and evaluating different proposals for allocating laboratory personnel to implement a program.     

Manpower planning for maintenance jobs in process industries

This paper describes a model for allocating the weekly requirement of manpower for maintenance jobs in the process units. We develop a simple procedure for the solution of the manpower allocation problem which has to deal with planned and unplanned jobs during a planning period. The solution procedure is illustrated by a numerical example. Possible extensions of this model are also discussed.     

An intelligent workstation controller for integrated planning and scheduling of FMS cell

This paper presents an experimental design developed to determine a combination of robust planning and scheduling rules for an intelligent workstation controller (IWC). The IWC is used as part of the control system for an automated flexible manufacturing system. A three-level hierarchical control structure (shop, workstation and equipment)is adopted in order effectively to control a shop-floor. At the top level is a shop controller which receives orders and their associated manufacturing information, and manages interactions among workstations. The IWC defines and resolves the production control activities necessary to coordinate a group of equipment controllers so as to ensure the completion of orders. Specifically, the IWC is responsible for selecting a specific process routeing for each part, allocating resources, scheduling and coordinating the activities across the equipment, monitoring the progress of activities, detecting and recovering from errors, and preparing reports. These activities are accomplished using planning, scheduling, and execution functions. In order to demonstrate the effectiveness and robustness of the IWC, all the controllable and uncontrollable factors need to be identified and detailed. Controllable factors are those which are set by the controller and cannot be directly affected by the production environment. Uncontrollable factors are those which vary with the production environment and cannot be directly changed by the controller developer. The objective of the paper is to illustrate how a good set of controllable factors that dictate the IWC's effectiveness and robustness over various uncontrollable factors can be determined. Due to the number of possible combinations of all the factors, a complete validation of the effectiveness and robustness of the IWC is extremely time consuming and far beyond the scope of this paper. Therefore, a few planning and scheduling strategies are selected and a formal experiment is conducted. The experiment illustrates how significant performance dependencies for various planning and scheduling strategies can be identified.     

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。     

The new health care civilization: integration of physician land and manageria

Changes occurring in health care demand that physicians expand their professional knowledge and skills beyond the medical and behavioral sciences. Subjects absent from traditional medical education curricula, such as the economics and politics of health care, practice management, and leadership of professional organizations, will become important competencies, particularly for physicians who serve in management roles. Because physicians occupy a central role in planning and allocating medical care services and other health care resources, they must be better prepared to work with other health care professionals to create a new civilization, even if this means leaving the cloistered domain of "physician land" to serve as interface professionals between the delivery of medical services and the management of health care. Our research findings and conclusions strongly suggest that economic, management, and leadership competencies need to be incorporated into the professional development of physicians, especially in postgraduate and continuing education curricula.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.     

The use of a model in long term planning—A case history

Long term planning in companies can range from the partial simplistic approach to a structured time-consuming ritual. Either extreme can bring planning into disrepute, and both reflect the lack of the proper tools of the trade. Models, by themselves, are no panacea, but properly conceived, constructed, and developed they can transform the planning process. The key to effective and practical models is use, and this can be achieved through direct management involvement on the model's development, and by making sure the model is basically simple and flexible. This article describes how such a model was constructed using a modular approach, and how it was used effectively in long term planning.