A hybrid heuristic approach to provider selection and task allocation problem in telecommunications with varying QoS levels

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In this research we examine a cost minimization problem for a firm that uses telecommunication networks to carry out their daily operations by acquiring network capacity from multiple providers. We consider a network environment where the firm can acquire network capacity with different service qualities and price points. We formulate the associated optimization problem considering quality and capacity requirements and offer a solution approach based on Genetic Algorithm (GA). Our model considers the tradeoff between the capacity acquisition cost and opportunity cost that occurs when target transmission rates in real-time tasks fall below a desired level. We model the capacity and the loss probability requirements explicitly and formulate delay and jitter as level matching constraints. We analyze how different prices, quality and task distribution affect the optimal behavior of the firm. We also compare three GA based heuristics and comment on the suitability of the GA approach for resource selection and task allocation problems.