The ontology of Operations Research and Complexity Theory : a critical analysis
Abstract
Operations Research (OR) refers to analytical and mathematical methods of problem-solving and decision-making. The Institute for Operations Research and the Management Sciences (INFORMS)1 defines OR simply as “a discipline that deals with the application of advanced analytical methods to help make better decisions”. Despite a number of recent studies in the area of systems thinking (Mingers and White 2010) and lately in Behavioural OR (Harmalainen et al. 2013) it appears that OR is still mainly inspired by a Newtonian framework that claims that the universe can be understood through a process of reductionism and breaking up of systems into parts in order to understand how the whole works. This viewpoint has been indicated and critiqued as early as 1962 by OR researchers such as R.L. Ackoff, who argues that OR is based on a mechanistic methodology. In fact, Ackoff claimed in 1979 that the “future of OR is past” because of this closed and mechanistic approach of “predict and prepare”. He lists six deficiencies to support his argument and contends that the OR methodology does not take into account the complexity of the large number of role players, their interactions and intricate relationships (Ackoff 1979a). The reductionist approach followed by OR practitioners may have worked in the past but more fitting paradigms for the present should also be considered and where appropriate, should replace the old paradigm of linearity. One such new paradigm may be found in Complexity Theory. Complexity Theory, although difficult to define, offers a new and different theoretical framework for the way in which certain systems can be understood. The late South African philosopher Paul Cilliers describes a complex system in terms of ten characteristics, such as being an open system consisting of a large number of elements that interact in a dynamic and non-linear way with each other (Cilliers 1998). Complex systems also exhibit other properties, such as emergence, boundaries, lack of complete knowledge and ethical issues. These characteristics and properties clearly indicate that a complex system cannot fully operate in the same paradigm of order in which OR traditionally operates. It can be argued that the majority of typical OR applications function in a complex reality which can be described in terms of the characteristics of a complex system. This study therefore proposes that OR can benefit from employing a complexity theory approach to its field so as to afford new fundamental insights to the methods for engaging with decision-making in the real-life context in which OR is used. This goal may be translated into the following hypothesis: By acknowledging that decision-making happens in a complex reality (with the characteristics as stated by Cilliers) and by verifying that the structures and environments in which OR approaches are applied are complex, new contributions could be made to the epistemology that fundamentally informs the field of OR.
In order to reach this goal – with the possibility of a fundamental change in how decision-makers view the process of OR based decision making – the study will start with a brief introduction and overview of OR and Complexity Theory. The development of both these fields are discussed and especially Ackoff’s critique regarding the short-comings of the traditional OR methods that are based on analytical and mathematical modelling so as to develop better optimisation models. It will then be argued that the traditional models that are used in OR are mainly assuming that the nature of the world is machine-like and that OR models assume that formal mathematical models can explain and predict the reality in which they are employed perfectly (positivism). To criticise and broaden this traditional OR approach (and to explain the shortcomings thereof in light of real life problems) Complexity Theory will be introduced and discussed (through the work of Paul Cilliers) as a way in which the complexity of the world is acknowledge. Based on the understanding that the world is not mechanical but complex in nature (as explained by Cilliers and the characteristics of complex phenomena), one sees that the assumptions on which traditional OR theories based their field of study are in many cases contentious and that the accompanying epistemology and related methods are limited and/or flawed. By aligning OR epistemologies with the acknowledgment of complexity, new methods for modelling decision making could be developed. In light of Complexity Theory, these methods should be cognisant of complexity characteristics such as emergence, boundary setting, provisional knowledge and what (ethical) responsibilities accompany such methods. Some concrete examples will therefore be given as part of this study of how OR could be influenced by applying a complexity lens. The overall focus will thus be, as the title suggests, on the epistemological implications of complexity thinking for OR. In accordance with rule A.7.2.5 of the “General Academic Rules” of the North-West University, this mini-dissertation is presented in the form of an article. The article will be presented for publication in the European Journal of Operational Research at a later stage (the guidelines for publication in this journal are included in the appendix). The article contains the following sections 1. Introduction 2. Operations Research: Epistemological questions 3. Complexity Theory: An alternative epistemology
4. Operations Research in the context of Complexity 5. The general reductionist epistemology of Operations Research
6. Aligning the epistemology of Operations Research with complexity 7. Conclusion. The next section presents the research article, with a bibliography and a summary in accordance with the prescriptions of the European Journal of Operational Research. In the final sections of this mini-dissertation some general conclusions, limitations and recommendations for further research are presented. The appendix contains the prescriptions for research articles submitted to the European Journal of Operational Research.
Collections
- Humanities [2671]