Part 2 book "Evolutionary scheduling" includes content: Optimum oil production planning using an evolutionary approach; a hybrid evolutionary algorithm for service restoration in power distribution systems; evolutionary generator maintenance scheduling in power systems; simultaneous planning and scheduling for multi autonomous vehicles; evolutionary optimization of business process designs; a genetic algorithm based reconfigurable scheduler. | Optimum Oil Production Planning using an Evolutionary Approach Tapabrata Ray1 and Ruhul Sarker2 1 School of Aerospace Civil and Mechanical Engineering 2 School of Information Technology and Electrical Engineering University of New South Wales at the Australian Defence Force Academy Northcott Drive Canberra 2600 Australia Email @ Summary. In this chapter we discuss a practical oil production planning problem from a petroleum field. A field typically consists of a number of oil wells and to extract oil from these wells gas is usually injected which is re- ferred as gas-lift. The total gas used for oil extraction is constrained by daily availability limits. The oil extracted from each well is known to be a nonlinear function of the gas injected into the well and varies between wells. The problem is to identify the optimal amount of gas that needs to be injected into each well to maximize the amount of oil extracted subject to the constraint posed by the daily gas availability. The problem has long been of practical interest to all major oil exploration companies as it has a potential of deriving large financial benefits. Considering the complexity of the problem we have used an evolutionary algorithm to solve various forms of the production planning problem. The multiobjective formulation is at- tractive as it eliminates the need to solve such problems on a daily basis while maintaining the quality of solutions. Our results show significant im- provement over existing practices. We have also introduced a methodology to deliver robust solutions to the above problem and illustrated it using the six-well problem. Furthermore we have also proposed a methodology to create and use a surrogate model within the framework of evolutionary op- timization to realistically deal with such problems where oil extracted from a well is a nonlinear function of gas injection and a piecewise linear model may not be appropriate. T. Ray and R. Sarker Optimum Oil .
