In this paper a fast analytical algorithm for design a surface-mounted PM Brushless DC motor (SMPM-BLDC) for variable-speed application based on electromagnetic field analysis and RSM optimization algorithm is discussed. To achieve the desired performance, the physical dimensions of the proposed SMPM-BLDC motor subject to minimal ripple torque utilizing RSM optimization algorithm were optimized...

In this paper the performance of four well-known metaheuristics consisting of Artificial Bee Colony (ABC), Biogeographic Based Optimization (BBO), Harmony Search (HS) and Teaching Learning Based Optimization (TLBO) are investigated on optimal domain decomposition for parallel computing. A clique graph is used for transforming the connectivity of a finite element model (FEM) into that of the cor...

Composite RCS building frames integrate reinforced concrete columns with structural steel beams to provide an efficient solution for the design and construction of earthquake-resisting structures. In this paper, an optimization framework is developed for performance-based seismic design of planar RCS moment resisting frames. The objective functions are defined as minimizing the construction cos...

Engineering optimization needs easy-to-use and efficient optimization tools that can be employed for practical purposes. In this context, stochastic search techniques have good reputation and wide acceptability as being powerful tools for solving complex engineering optimization problems. However, increased complexity of some metaheuristic algorithms sometimes makes it difficult for engineers t...

In this paper, a systematic framework for synthesis and design of processing networks under uncertainty is presented. Through the framework, an enterprise-wide optimization problem is formulated and solved under uncertain conditions, to identify the network (composed of raw materials, process technologies and product portfolio) which is feasible and have optimal performances over the entire unc...

In many real applications, especially those involving data objects with complicated semantics, it is generally desirable to discover the relation between patterns in the input space and labels corresponding to different semantics in the output space. This task becomes feasible with MIML (Multi-Instance Multi-Label learning), a recently developed learning framework, where each data object is rep...

Low-cost massively parallel architectures are generally characterized by a limited amount of memory owned by each Processing Element. As a consequence, low-cost mesh-connected architectures can utilize only a speciic processor virtualization mechanism which is based on the sequential scanning of the data set stored in an external memory. As a consequence of this virtualization mechanism, applic...

Global optimization of the energy consumption in heterogeneous environments has been recently an important research issue in wired and wireless networks. This paper presents a general framework for flexible and cognitive backbone network management which leads to the minimization of the energy utilized by the network. The policy for activity control of all the modules and elements that form a n...

Similarity search in math is to find mathematical expressions that are similar to a user’s query. We conceptualized the similarity factors between mathematical expressions, and proposed an approach to math similarity search (MSS) by defining metrics based on those similarity factors [11]. Our preliminary implementation indicated the advantage of MSS compared to nonsimilarity based search. In or...