TY  - JOUR
T1  - Emission/Economic Load Dispatch Using Combination of Evolutionary Algorithms
AU - A. El-Fergany, Attia AU - El-Arini, Mahdi 
JO  - International Journal of Soft Computing
VL  - 7
IS  - 5
SP  - 256
EP  - 263
PY  - 2012
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2012.256.263
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2012.256.263
KW  - Emission
KW  -evolutionary algorithms
KW  -load dispatch
KW  -mutli-objective function
KW  -Egypt
AB  - This study presents an integrating Genetic Algorithm (GA) 
  and Pattern Search (PS) approaches to solve the Combined Emission/Economic Dispatch 
  (CEED) problems with multi-objectives have been developed. This integration 
  will combine the strengths of GA and PS to solve this problem. The PS performance 
  is highly dependent on the initial/starting point. To tackle this issue, GA 
  was utilized to initiate the starting point for PS and to validate the obtained 
  result of PS as well. The weighted multi-objective function with penalty factor 
  is used in this study. The proposed weighting factor plays significant part 
  on the problem solution. The proposed methodology considers operational power 
  constraints of generating units, value-point loading ripple effects with non-convex 
  characteristics and line losses as well for practical applications. The proposed 
  integrating algorithms were intensively demonstrated, tested and verified on 
  several cases. The obtained results prove high quality and effectiveness of 
  proposed integrated GA-PS algorithm to solve CEED problems with reduced execution 
  time.
ER  -