نتایج جستجو برای: imperilist competitive algorithm ica
تعداد نتایج: 839834 فیلتر نتایج به سال:
A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective functi...
Template matching is a widely used technique in many of image processing and machine vision applications. In this paper we propose a new as well as a fast and reliable template matching algorithm which is invariant to Rotation, Scale, Translation and Brightness (RSTB) changes. For this purpose, we adopt the idea of ring projection transform (RPT) of image. In the proposed algorithm, two novel s...
increasing of the distribution efficiency is one of the most objectives of an integrated logistic system developed as a new management philosophy in the past few decades. the problem is examind in two parts: facilities location problem (flp) for long policies and vehicle routing problem (vrp) to meet the customer demand. these two components can be solved separately; however, this solution may ...
Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs. In this paper, just-in-time (JIT) flow shop scheduling problem with preemp...
The article presents the hybrid metaheuristic-neural assessment of the pull-off adhesion in existing multi-layer cement composites using artificial neural networks (ANNs) and the imperialist competitive algorithm (ICA). The ICA is a metaheuristic algorithm inspired by the human political-social evolution. This method is based solely on the use of ANNs and two non-destructive testing (NDT) metho...
This paper presents a computational intelligence approach for coping with bullwhip effect in supply chains (SCs). An imperialist competitive algorithm (ICA) is employed to decrease the bullwhip effect and cost (inventory, ordering and production) in the MIT beer distribution game. The ICA is used to determine the optimal ordering policy for members of the SC. The results shows the ability of th...
The im perialist competitive algorithm (ICA) is a new h euristic algorithm proposed for continuous optim ization problems. The research about its application on solving the traveling salesm an problem (TSP) is still very lim ited. Aiming to explore its ability on solving TSP, we present a discrete im perialist competitive algorithm in this paper. The proposed algorithm modifies the original rul...
In this paper, a two-surfaces sliding mode controller (TSSMC) is proposed for the voltage tracking control of a two input DC-DC converter in application of electric vehicles (EVs). The imperialist competitive algorithm (ICA) is used for tuning TSSMC parameters. The proposed controller significantly improves the transient response and disturbance rejection of the two input converters while p...
this paper presents an accurate differential global positioning system (dgps) using multi-layered neural networks (nns) based on the back propagation (bp) and imperialistic competition algorithm (ica) in order to predict the dgps corrections for accurate positioning. simulation results allowed us to optimize the nn performance in term of residual mean square error. we compare results obtained b...
In this paper, the recently introduced optimisation strategy, imperialist competitive algorithm (ICA) is used to design an optimal antenna array which minimises the error probability for binary phase shift keying modulation, called minimum bit error rate (MBER) beamforming. ICA is used to deal with the high complexity and high dimensionality of this challenging problem which can not be easily s...
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