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Search Results: 1 - 4 of 4 matches for " Hardiansyah "
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Artificial Bee Colony Algorithm for Economic Load Dispatch Problem
Hardiansyah Hardiansyah
IAES International Journal of Artificial Intelligence (IJ-AI) , 2013, DOI: 10.11591/ij-ai.v2i2.1613
Abstract: In practical cases, the fuel cost of generators can be represented as a quadratic function of real power generation and satisfied constraints for minimizing of fuel cost. Artificial Bee Colony (ABC) algorithm is used for the optimization of active power dispatch of generating units. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total cost is minimized. Simulation and analysis of economic load dispatch using Artificial Bee Colony (ABC) algorithm is proposed. The obtained results are compared with the conventional method, genetic algorithm (GA) and shows that the ABC algorithm approach is more feasible and efficient for finding minimum cost.
Cross Entropy Method for Solving Generalized Orienteering Problem  [PDF]
Budi Santosa, Nur Hardiansyah
iBusiness (IB) , 2010, DOI: 10.4236/ib.2010.24044
Abstract: Optimization technique has been growing rapidly throughout the years. It is caused by the growing complexity of problems that require a relatively long time to solve using exact optimization approach. One of complex problems that is hard to solve using the exact method is Generalized Orienteering Problem (GOP), a combinatorial problem including NP-hard problem. Recently, there has been plenty of heuristic method development to solve this problem. This research is an implementation of cross entropy (CE) method in real case of GOP. CE is an optimization technique that relatively new, using two main procedures; generating sample solution and parameter updating to produce better sample for next iteration. At this research, GOP problem that occurs at finding optimal route consist of 27 cities in eastern China is investigated. Results indicate that CE method give better performance than those of Artificial Neural Network (ANN) and Harmony Search (HS).
Multiobjective H2/H? Control Design with Regional Pole Constraints
Hardiansyah Hardiansyah,Junaidi Junaidi
TELKOMNIKA : Indonesian Journal of Electrical Engineering , 2012, DOI: 10.11591/telkomnika.v10i1.659
Abstract: This paper presents multiobjective H2/H? control design with regional pole constraints. The state feedback gain can be obtained by solving a linear matrix inequality (LMI) feasibility problem that robustly assigns the closed-loop poles in a prescribed LMI region. The proposed technique is illustrated with applications to the design of stabilizer for a typical single-machine infinite-bus (SMIB) power system. The LMI-based control ensures adequate damping for widely varying system operating conditions. The simulation results illustrate the effectiveness and robustness of the proposed stabilizer.
Solving Economic Load Dispatch Problem Using Particle Swarm Optimization Technique
Hardiansyah,Junaidi,Yohannes MS
International Journal of Intelligent Systems and Applications , 2012,
Abstract: Economic load dispatch (ELD) problem is a common task in the operational planning of a power system, which requires to be optimized. This paper presents an effective and reliable particle swarm optimization (PSO) technique for the economic load dispatch problem. The results have been demonstrated for ELD of standard 3-generator and 6-generator systems with and without consideration of transmission losses. The final results obtained using PSO are compared with conventional quadratic programming and found to be encouraging.
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