An innovative simulated annealing approach to the long-term hydroscheduling problem
This paper presents a new simulated annealing algorithm (SAA) to solve the long-term hydro scheduling problem (LTHSP). A new algorithm for randomly generating feasible trial solutions is introduced. The problem is a hard nonlinear optimization problem in continuous variables. An adaptive cooling sch...
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| التنسيق: | article |
| منشور في: |
2001
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/14845/1/14845_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14845/2/14845_2.doc |
| الوسوم: |
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| الملخص: | This paper presents a new simulated annealing algorithm (SAA) to solve the long-term hydro scheduling problem (LTHSP). A new algorithm for randomly generating feasible trial solutions is introduced. The problem is a hard nonlinear optimization problem in continuous variables. An adaptive cooling schedule and a new method for variables discretization are implemented to enhance the speed and convergence of the original SAA. A significant reduction in the number of the objective function evaluations, and consequently less iterations are required to reach the optimal solution. The proposed algorithm has been applied successfully to solve a system with four series cascaded reservoirs. Numerical results show an improvement in the solutions compared to previously obtained results |
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