Category: Algorithms and Programming Copyright © 2014, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. 1030 GA Based FGP to Solve BLP Model of EEPGD Problem INTRODUCTION The demand of electric power has increased in alarming rate in recent years owing to rapid growth of human development index across the countries in modern world. It is to be mentioned here that the main supply source of electric energy is ther- mal power plant, where fossil-fuel used as main power generation resource, discharges emissions to earth’s environment. The thermal power genera- tion problems are actually optimization problems with multiplicity of objectives and various system constraints in the environment of generation of power. The two most important objectives associ- ated with the problem are minimization of power generation cost and environmental emission. The general mathematical programming (MP) model for optimal power generation decision was introduced by Dommel, & Tinney (1968). The deep study made in the field in the past century was surveyed by (Momoh, El-Hawary, & Adapa, 1999). The constructive optimization model for minimization of thermal power plant emissions was first studied by Gent, & Lament (1971). Here, it is to be noted that the objectives of such a problem are incommensurable in nature and often conflict each other in optimizing them in actual practice. As such, a balanced decision could not be achieved there concerning simulta- neous optimization of objectives. To overcome the difficulty, Goal Programming (GP) (Lin, 1980) approach as a robust and flexible tool for multiobjecive decision analysis was employed to economic-environmental power generation and dispatch (EEPGD) problem (Nanda, Kothari, & Lingamurthy, 1988) to obtain goal-oriented solu- tion in a crisp environment. However, in most of the practical decision situ- ations, it is to be observed that decision parameters of problems with multiplicity of objectives are inexact in nature owing to inherent impressions in parameter themselves as well as imprecise in nature of human judgments of setting parameter values. To cope with the situation, Fuzzy program- ming (FP) approach (Zimmermann, 1987) based on Fuzzy Set Theory (Zadeh, 1965) to EEPGD problems have been discussed (Wang, & Singh, 2007) in the past. Further, to overcome the com- putational difficulty with nonlinear and competi- tive in nature of objectives, genetic algorithms (GAs) (Deb, 2002) based on natural selection and natural genetics have also been employed to EEPGD problems (Abido, 2003; Gong, Zhang, & Qi, 2010). But, deep study in this area is at an early stage. Now, it is to be observed that the objectives of minimizing power generation cost and environ- mental emission highly conflict each other owing to current accelerating demand rate of electricity as well as increasing social pressure for control- ling pollutions. As an essence, optimization of objectives in a hierarchical structure on the basis of needs of decision maker (DM) can be consid- ered. As such, bilevel programming (BLP) (Pal, & Moitra, 2003) in hierarchical decision system might be an effective one for solving EEPGD problems. Although, the problem of balancing thermal power supply and market demand have Bijay Baran Pal University of Kalyani, India Papun Biswas JIS College of Engineering, India DOI: 10.4018/978-1-4666-5202-6.ch094