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A genetic algorithm that utilizes process algebra for coding of solution chromosomes and for defining evolutionary based operators is presented. The algorithm is applicable to mission planning and optimization problems. As an example the high level mission planning for a cooperative group of uninhabited aerial vehicles is investigated. The mission planning problem is cast as an assignment problem, and solutions to the assignment problem are given in the form of chromosomes that are manipulated by evolutionary operators. The evolutionary operators of crossover and mutation are formally defined using the process algebra methodology, along with specific algorithms needed for their execution. The viability of the approach is investigated using simulations and the effectiveness of the algorithm is shown in small, medium, and large scale problems.