Foundations of Operational Research and Business Analysis 1
Author: Thibaut Achard de Leluardière
Looking through the infinite number of theories and models developed in organisations, this assignment aims at finding out the founding principles of a good OR/MS model and general issues encountered in the setting-up of OR interventions. To try out and compare the insights presented, this assignment proposes to study a specific case about OR modelling in Fishery management. Fishery Management is related to the preservation of fish resources and optimisation of catch and profit of this industry, in a context of high-yield practices and increasingly more ...view middle of the document...
The article provides two different equation models aiming at simulating fishing behaviours in order to optimize fishing policies. The study is based on data from Canadian fisheries of Nova Scotia, which is one of Canada’s Maritime Provinces. Fishery management modelling is based on the assumption that there is a maximum economic yield to maintain through a system of catches limitation or restricted fishing licences.
The first model is a simple, non-spatial dynamic model for a single specie of fish. It studies the evolution over time of catch rate and fishing efforts in response to revenue and profits obtainable, under the effects of natural fluctuations of fish resources. Different rates of answer are tested. Haddock is chosen over the other species because it is the highest price fish. Thus it ensures causality between fishing efforts and specie density. An equation can modelize the close relationship between predator, fishermen represented by the growth of fishing effort, and the prey population, fishes. The equation is randomly tested with different economic factors related to demand, profitability, and boats in competition, and biologic factors such as the age and weight of fishes, and also the fluctuations of birth rate of the specie, which vary from year to year. The model showed in this article point out the fact that human responses can amplify relatively small annual environmental situations, leading to large, quasi cyclic changes in catch and profit.
The second model adds a spatial factor and includes all kind of species in the analysis provided. This second model attaches more importance on the behavioural aspect of fishermen and the role of information and knowledge to analyse their fish efficiency. It puts the emphasis on the level of rationality they adopt in the way they make decision on where and what to fish. It distinguishes to types of skippers: those adopting a ‘stochasts’ behavourial strategy and ‘cartesians’. ‘Stochasts’ are risk-takers and try to discover new attractive fish zones. ‘Cartesians’ do not take the risk of moving outside of their zone and muster their efforts until they have exploited it completely. The model divides the fishing area in 19 equal spatial zones with different distributions of fish in dollars value. Several random tests are made depending on the presence and competition between ‘stochast’ and ‘cartesians’, and the impact of technologies on the exchange of information between them. This model tends to demonstrate that stochastic behaviours are necessary for the survival of the fishery, and that the efficiency and size of the industry depends on the level of information flows concerning catch.
My personal analytical project is related to an internship I fulfilled at the French Headquarter of ExxonMobil, in the commercial downstream department. I got an experience in an analytical project for commercial purposes, by conducing a portfolio segmentation of a particular type of customers called net...