1              !  Ajay Dashora 1 , Bharat Lohani 1 and Kalyanmoy Deb 2 1 Department of Civil Engineering, 2 Department of Mechanical Engineering Indian Institute of Technology Kanpur PIN 208016, Uttar Pradesh, India {ajayd,blohani,deb}@iitk.ac.in "# !  $ # % &’()’(& http://www.iitk.ac.in/kangal/pub.htm * Genetic algorithms (GA) are being widely used as an evolutionary optimization technique for solving optimization problems involving non7differentiable objectives and constraints, large dimensional, multi7modal, overly constrained feasible space and plagued with uncertainties and noise. However, to solve different kinds of optimization problems, no single GA works the best and there is a need for customizing a GA by using problem heuristics to solve a specific problem. For the airborne flight planning problem, there is not much prior optimization studies made using any optimization procedure including a GA. In this paper, we make an attempt to devise a customized GA for solving the particular problem to arrive at a reasonably good solution. A step7by7step procedure of the proposed GA is presented and every step of the procedure is explained. Both single and multi7objective versions of the problem are solved for a particular scenario of the flight planning for airborne LiDAR data acquisition problem to demonstrate the use of a GA for such a real7world problem. The deductive approach successfully identifies the appropriate configurations of GA. The paper demonstrates how a systematic procedure of developing a customized optimization procedure for solving a real7world problem involving mixed variables can be devised using an evolutionary optimization procedure. (+ , Over the past two decades, there had been remarkable developments in the field of evolutionary algorithms for solving real7world and complex optimization problems.