Implementation of the operations research/management science process

The aim of this article is to point out some basic aspects of the OR/MS implementation problem and to outline a frame of reference for dealing with the OR/MS process. The model proposed includes a decomposition of the OR/MS process. Phases, interest groups, strategies, and variables in the OR/MS process are considered as being important. The first part of the article is a summary of some important recent contributions by others, whereas the second part represents contributions resulting from the author's own research.     

OR/MS research in disaster operations management

Disasters are large intractable problems that test the ability of communities and nations to effectively protect their populations and infrastructure, to reduce both human and property loss, and to rapidly recover. The seeming randomness of impacts and problems and uniqueness of incidents demand dynamic, real-time, effective and cost efficient solutions, thus making the topic very suitable for OR/MS research. While social sciences and humanities literatures enjoy an abundance of articles on disaster management, the OR/MS community is yet to produce a critical mass. In this paper, we survey the literature to identify potential research directions in disaster operations, discuss relevant issues, and provide a starting point for interested researchers.     

The changing role of analysts in effective implementation of operations research and management science

The implementation of operations research findings is a major obstacle to increased use of operations research by management. A number of researchers have used a research approach called the factor paradigm. We appear to need an approach which focuses on the dynamics of implementation. A recognition of the different roles of the analyst would help improve the interplay between analyst and client system. A number of roles are discussed in the article, including the role of the expert, systemizer, sparring partner, process consultant, and communicator.     

Fisheries management and operations research

Fisheries are subject to a deep-rooted problem of economic inefficiency, often referred to as the fisheries problem. The fisheries problem derives fundamentally from inappropriate social institutions controlling the fishing activity, the foremost of which is the common property arrangement. Fisheries management consists of replacing these institutions with more appropriate ones. Which institutions are most appropriate depends on the social objectives of the fisheries. There are strong economic arguments for the view that there should be only a single objective, namely to maximize the present value of the flow of benefits from the fisheries. In reality, different interest groups often push for several, often conflicting, objectives. In that case a multi-objective programming approach may be appropriate.     

Review of recent developments in OR/MS research in disaster operations management

Potential consequences of disasters involve overwhelming economic losses, large affected populations and serious environmental damages. Given these devastating effects, there is an increasing interest in developing measures in order to diminish the possible impact of disasters, which gave rise to the field of disaster operations management (DOM). In this paper we review recent OR/MS research in DOM. Our work is a continuation of a previous review from Altay and Green (2006). Our purpose is to evaluate how OR/MS research in DOM has evolved in the last years and to what extent the gaps identified by Altay and Green (2006) have been covered. Our findings show no drastic changes or developments in the field of OR/MS in DOM since the publication of Altay and Green (2006). Additionally to our comparative analysis, we present an original evaluation about the most common assumptions in recent OR/MS literature in DOM. Based on our findings we provide future research directions in order to make improvements in the areas where lack of research is detected.     

Strategic financial risk management and operations research

Risk management has become a vital topic for financial institutions in the 1990s. Strategically, asset/liability management systems are important tools for controlling a firm's financial risks. They manage these risks by dynamically balancing the firm's asset and liabilities to achieve the firm's objectives. We discuss such leading international firms as Towers Perrin, Frank Russell, and Falcon Asset Management, which apply asset/liability management for efficiently managing risk over extended time periods. Three components of asset/liability management are described: 1) a multi-stage stochastic program for coordinating the asset/liability decisions; 2) a scenario generation procedure for modeling the stochastic parameters; and 3) solution algorithms for solving the resulting large-scale optimization problem.     

Perspectives on operations research in data and knowledge management

A number of problems in the design and management of database systems and knowledge base systems (KBSs) can be addressed using techniques from operations research (OR). This article provides a perspective on these problems and the types of models that have been applied to them, and identifies some areas that pose interesting modeling and analysis questions for researchers working in areas such as mathematical programming, stochastic modeling, dynamic programming and simulation.     

Improving company operations Operations planning/operations research consultancy in Unilever Germany

After a discussion of the attributes of the operational researcher and the manager required for success, the organisation and philosophy of OPOR are described. This is followed by examples to illustrate how the internal consultancy approach is transposed into every day studies.     

Exercising QS: quantitative skills in an exercise science course

This study seeks to bring the discipline of exercise science into the discussion of Quantitative Skills (QS) in science. The author's experiences of providing learning support to students and working with educators in the field are described, demonstrating the difficulty of encouraging students to address their skills deficit. A survey of students’ perceptions of their own QS and of that required for their course, demonstrates the difficulties faced by students who do not have the prescribed assumed knowledge for the course. Limited results from academics suggest that their perceptions of students’ QS deficits are even direr than those of the under-prepared students.     

Model validation in operations research

Numerous articles have appeared in the literature expressing different degrees of concern with the methodology of OR in general and with the validation of OR models in particular. Suggestions have been formulated to remove some of the shortcomings of the methodology as currently practised and to introduce modifications in the approach because of the changing nature of the problems tackled. Advances in modeling capabilities and solution techniques have also had considerable impact on the way validation is perceived. Large scale computer-based mathematical models and especially simulation models have brought new dimensions to the notion of validation. Terms like ‘confidence’, ‘credibility and reliability’, ‘model assessment and evaluation’, ‘usefulness and usability of the model’ have become rather common. This paper is an attempt, through an interpretation of the literature, to put model validation and related issues in a framework that may be of use both to model-builders and to decision-makers.     

Reassessing operations research in Finland

At the beginning of 1980 the Finnish Operations Research Society (FORS) established a working group (OTSA) headed by Y. Seppälä. The aim was to analyse R.L. Ackoff's and others' criticism of operations research in order to make improvement proposals for the Finnish operations research. The final report of this working group was completed in December 1981.Within this project an analysis was made of opinions of members of the Finnish Operations Research Society concerning their own work and role. It was found to be a drawback that the Finnish operations research has been too much concerned with well defined problems, neglecting truly challenging ‘wicked’ problems. Accordingly, the main recommendation of the group is that besides operations researchers concerned with well structured problems we should also train systems analysts to deal essentially with poorly defined problems.This article will provide a profile of the Finnish operations researchers as reflected in the survey. An analysis of the crisis in operations research will be given as well as a portrayal of the roles for operations researcher and systems analyst. The paper concludes by presenting various working methods of systems analysts on the basis of the final report by the OTSA group.     

Issues in the use of ratings-based versus choice-based conjoint analysis in operations management research

Conjoint analysis has played an important role in helping make a number of operations management decisions including product and service design, supplier selection, and service operations capacity. Many recent advances in this area have raised questions about the most appropriate form of conjoint analysis for this research. We review recent developments in the literature and provide new evidence on how the choice between ratings- and choice-based conjoint models might affect the estimates of customer demand used in operations management models.     

Information in the operations research process

The article deals with information in the OR process. The value of an ‘optimal’ model solution which is not implemented is not very high. Many errors are due to a too narrow formulation of the problem, often a formulation which has focused on purely technical and economic aspects, or a formulation which has been adapted for a standard model. The concepts and models treated in the article take their point of departure in the actual problem. The models can be used as a frame of reference by various individuals and groups which are involved in OR work.     

Integrating operations research in constraint programming

This paper presents constraint programming (CP) as a natural formalism for modelling problems, and as a flexible platform for solving them. CP has a range of techniques for handling constraints including several forms of propagation and tailored algorithms for global constraints. It also allows linear programming to be combined with propagation and novel and varied search techniques which can be easily expressed in CP. The paper describes how CP can be used to exploit linear programming within different kinds of hybrid algorithm. In particular it can enhance techniques such as Lagrangian relaxation, Benders decomposition and column generation.     

Experiences in Developing an Expert System for MBA Admissions

An expert system to assist in admitting students onto a part-time postgraduate course has been developed through three phases, using an expert systems shell. The first phase was an unstructured approach, which demonstrated the feasibility of the system but led to difficulties in development. The second phase followed a simplified systems analysis and resulted in a more comprehensive and structured system. However, its operation was cumbersome and unfriendly. The third phase involved developing a mathematical model of the decision-maker's judgement and led to a simpler, more effective and easier to use system.