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In this paper, based on the Quantum-behaved Particle Swarm Optimization algorithm, we evolve the algorithm to optimize a multiobjective optimization problem, namely the Cobb Douglas Habitability function which is based on CES production functions in Economics. We also propose some changes to the Quantum-behaved Particle Swarm Optimization algorithm to mitigate the problem of the algorithm prematurely converging and show the results of the proposed changes to the Quantum-behaved Particle Swarm Optimization.

This paper describes how integrated energy-emissions planning can be carried out for evolving energy strategies that facilitate greenhouse gas mitigation. The India case study highlights different energy scenarios, keeping in view the need for clean environment. This study has been carried out using an integrated energy planning tool which takes emissions into account. The importance of energy efficiency, fuel switching, and utilization of hydro, nuclear and renewable energy sources, for greenhouse gas mitigation is clearly brought out. These findings would be of interest to those working on national energy planning, sustainable development, and climate change mitigation.