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The petroleum industry uses helicopters to transport employees to and from the offshore installations. The helicopter transportation represents a major risk for the employees. The helicopter routing problem is an application of vehicle routing problem with combined pickup and delivery demands, which usually minimizes the total cost of the routes and the fleet size (the number of routes) in a classical form. It is also of interest to minimize the transportation risk. In this paper, a multi-objective genetic algorithm is presented for the helicopter routing problem. The algorithm uses a variation of the cluster-first route-second method for routing helicopters. We apply the proposed algorithm to instances derived from real data and evaluate its effectiveness by comparing withε-constraint approach with a state-of-the-art single-objective tabu search metaheuristic.

GENETIC ALGORITHM FOR SOLVING A MULTI-OBJECTIVE HELICOPTER ROUTING PROBLEM