Search for: optimal-scheme
Article Physical Review A - Atomic, Molecular, and Optical Physics ; Volume 93, Issue 1 , 2016 ; 10502947 (ISSN) ; Karimipour, V ; Sharif University of Technology
American Physical Society
We propose a no-go theorem by proving the impossibility of constructing a deterministic quantum circuit that iterates a unitary oracle by calling it only once. Different schemes are provided to bypass this result and to approximately realize the iteration. The optimal scheme is also studied. An interesting observation is that for a large number of iterations, a trivial strategy like using the identity channel has the optimal performance, and preprocessing, postprocessing, or using resources like entanglement does not help at all. Intriguingly, the number of iterations, when being large enough, does not affect the performance of the proposed schemes
Article ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE), 3 November 2017 through 9 November 2017 ; Volume 1 , 2017 ; 9780791858349 (ISBN) ; Shoureshi, P ; Soltani, M. R ; Khajeh Fard, A ; ASME ; Sharif University of Technology
The S-shaped air intakes are very common shapes due to their ease in the engine-body integration or Radar Cross Section, RCS, specifications especially for fighter aircrafts. The numerical shape optimization of an S-shaped air intake using adjoint method is conducted. The flow of a specified air intake that uses S-duct M2129 is simulated using three dimensional (3D) numerical solution of Reynolds-Averaged Navier-Stokes equation along with k-ω SST turbulence model. The main purpose of this optimization scheme is to maximize the total pressure recovery (TPR). Further, the scheme is developed in such a way that would be applicable in industry thru satisfying specified constraint requirements....
Article International Journal of Electrical Power and Energy Systems ; Volume 43, Issue 1 , 2012 , Pages 1094-1105 ; 01420615 (ISSN) ; Ehsan, M ; Fattahi Meyabadi, A ; Sharif University of Technology
This paper presents a dynamic multi objective model for distribution network expansion, considering the distributed generators (DGs) and network reinforcements. The proposed model simultaneously optimizes three objective functions namely, total cost, emission cost and technical satisfaction (voltage profile) by finding the optimal schemes of timing, sizing, placement and DG technologies in a long term planning period (dynamic planning). The importance of each objective function can be changed in the interactive steps. The calculation algorithm is based on Chaotic Local Search with Modified Honey Bee Mating Optimization (CLSMHBMO). The effectiveness of the proposed model and the calculation...
Hybrid immune-genetic algorithm method for benefit maximisation of distribution network operators and distributed generation owners in a deregulated environment, Article IET Generation, Transmission and Distribution ; Volume 5, Issue 9 , 2011 , Pages 961-972 ; 17518687 (ISSN) ; Ehsan, M ; Caire, R ; Hadjsaid, N ; Sharif University of Technology
In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution...
Article International Journal of Innovative Computing, Information and Control ; Volume 8, Issue 6 , 2012 , Pages 4157-4175 ; 13494198 (ISSN) ; Ehsan, M ; Meyabadi, A. F ; Niknam, T ; Sharif University of Technology
This paper presents a short term multi-objective planning model for Distributed Generators (DGs) deployment in an electrical network. "Total Cost" and "Emission Cost" are two objective functions which have been going to be minimized in this model by finding the optimal schemes of sizing, placement and DG technologies over a short planning period (static planning). The proposed model can be used for a long term planning period (dynamic planning) in order to consider the timing concept. An interactive fuzzy satisfying method based on Chaotic Local Search and Modified Honey Bee Mating Optimization (CLS-MHBMO) is used to choose the final solution. The effectiveness of the proposed model and...
A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources, Article Renewable Energy ; Volume 36, Issue 1 , 2011 , Pages 179-188 ; 09601481 (ISSN) ; Ehsan, M ; Zareipour, H ; Sharif University of Technology
This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models
Efficiency enhancement of optimized Latin hypercube sampling strategies: Application to Monte Carlo uncertainty analysis and meta-modeling, Article Advances in Water Resources ; Volume 76 , 2015 , Pages 127-139 ; 03091708 (ISSN) ; Ataie Ashtiani, B ; Janssen, H ; Sharif University of Technology
The majority of literature regarding optimized Latin hypercube sampling (OLHS) is devoted to increasing the efficiency of these sampling strategies through the development of new algorithms based on the combination of innovative space-filling criteria and specialized optimization schemes. However, little attention has been given to the impact of the initial design that is fed into the optimization algorithm, on the efficiency of OLHS strategies. Previous studies, as well as codes developed for OLHS, have relied on one of the following two approaches for the selection of the initial design in OLHS: (1) the use of random points in the hypercube intervals (random LHS), and (2) the use of...
A distribution network expansion planning model considering distributed generation options and techo-economical issues, Article Energy ; Volume 35, Issue 8 , 2010 , Pages 3364-3374 ; 03605442 (ISSN) ; Ehsan, M ; Sharif University of Technology
This paper presents a dynamic multi-objective model for distribution network expansion, considering the distributed generations as non-wire solutions. The proposed model simultaneously optimizes two objectives namely, total costs and technical constraint satisfaction by finding the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on DG units and/or network reinforcements over the planning period. An efficient heuristic search method is proposed to find non-dominated solutions of the formulated problem and a fuzzy satisfying method is used to choose the final solution. The effectiveness of the proposed model and search method are assessed and...
Multi-objective planning model for integration of distributed generations in deregulated power systems, Article Iranian Journal of Science and Technology, Transaction B: Engineering ; Volume 34, Issue 3 , 2010 , Pages 307-324 ; 10286284 (ISSN) ; Ehsan, M ; Sharif University of Technology
This paper presents a long-term dynamic multi-objective model for distributed generation investment. The proposed model optimizes three objectives, namely active losses, costs and environmental emissions and determines the optimal schemes of sizing, sitting of DG units and specially the dynamics of investment over the planning period. The Pareto optimal solutions of the problem are found using a GA algorithm and finally a fuzzy satisfying method is applied to select the optimal solution considering the desires of the planner. The solutions of Pareto optimal front are analyzed to extract general useful information for planners about the appropriate DG technologies and placement schemes. The...