Strategic Optimization and Contingency Planning Model for Oil Spill Response

Abstract

Proposal Response to marine pollution incidents requires careful advance planning to ensure that the impact of the pollution is minimized. A high priority must be given to developing contingency plans that will ensure prompt response to mitigate the adverse effect of any spill. Oil spill response planning will prescribe actions that will be performed under emergency conditions and attempts to minimize damage to the ecology and to the quality of human life. This paper deals with strategic optimization model that prescribe a minimum total cost plan to build new storage location and/or expand existing ones and to purchase new equipments and pre-position them and a contingency plan which determines what systems must be allocated to enable an effective response for each likely oil spill scenario. To date few studies have addressed the strategic aspect of oil spill cleanup management. The spill optimization models can contribute with contingency plans that are prepared by responsible parts in case of a spill and could be used as decision aid by all of these parts. They can be applied whenever new equipments are purchased or whenever any responsible party is preparing a contingency plan. In this paper is described a model that deals with modern oil spill cleanup requirements that include time-phased response. The model proposed considers further where to locate the protection systems that must be deployed to the priority areas associated with spill scenarios immediately after a spill occurs. The model is applied in a case that involves three companies that wish to update their contingency plan using the services of one spill response company. This response company will use the strategic response model for oil spills, in order to help it to check whether it's necessary to expand its response structure, and if so, the model will help to outline a lower-cost configuration that will be adequate to the new situation, fulfilling the legislation requirements. This model can be adopted by industry to facilitate contingency planning.