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Proceedings ArticleDOI

Lifetime Improvement of Digital Microfluidic Biochips based on the Improved Whale Optimization Algorithm for Protein Analysis Instrument System

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TLDR
An improved whale optimization algorithm (IWOA) is proposed, which can reduce excessive use of an electrode and reuse electrodes in average manner to optimal the longest lifetime of DMFBs during the design process.
Abstract
Digital micro-fluidic biochips (DMFBs) are revolutionizing laboratory procedures for point-of-care clinical diagnostics, environmental monitoring, and protein analysis. Those procedures require high precision of the output for every operation so it need to ensure the chip reliability and the chip lifetime. Because the electrodes on the chip may be reused at different experimental stages, a degraded electrode may be reused for many times. So the lifetime of the chips is closely related to the total actuating time of an electrode. Thus, the electrode total actuating time needs to be considered carefully in an efficient DMFBs design process. This paper proposed an improved whale optimization algorithm (IWOA), which can reduce excessive use of an electrode and reuse electrodes in average manner to optimal the longest lifetime of DMFBs during the design process. Firstly, the position mass of individual whales was improved to solve the problem that the data, calculated by the WOA, cannot be directly used to represent the sequence of operations. Secondly, the inertial weight was added to enhance the local search ability of WOA. The simulation experimental results showed that this algorithm was able to solve lifetime optimization problems. The maximum electrode time used was reduced by 10% to 20%. The performance of efficiency and convergence of algorithm were very good.

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Citations
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Journal ArticleDOI

A Routing-Based Repair Method for Digital Microfluidic Biochips Based on an Improved Dijkstra and Improved Particle Swarm Optimization Algorithm.

TL;DR: The routing problem is identified as a dynamic path-planning problem and mixed path design problem under certain constraints, and an improved Dijkstra and improved particle swarm optimization (ID-IPSO) algorithm is proposed, which can accommodate more faulty electrodes for the same fault repair rate.
References
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Journal ArticleDOI

The Whale Optimization Algorithm

TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.
Journal ArticleDOI

Optimizing connection weights in neural networks using the whale optimization algorithm

TL;DR: The qualitative and quantitative results prove that the proposed WOA-based trainer is able to outperform the current algorithms on the majority of datasets in terms of both local optima avoidance and convergence speed.
Journal ArticleDOI

Parameter estimation of photovoltaic cells using an improved chaotic whale optimization algorithm

TL;DR: The Chaotic Whale Optimization Algorithm (CWOA) is proposed, using the chaotic maps to compute and automatically adapt the internal parameters of the optimization algorithm for the parameters estimation of solar cells.
Journal ArticleDOI

Optimal siting of capacitors in radial distribution network using Whale Optimization Algorithm

TL;DR: In this article, the Whale Optimization Algorithm (WOA) is used to find optimal sizing and placement of capacitors for a typical radial distribution system, which is validated by applying it on standard radial systems: IEEE-34 bus and IEEE-85 bus radial distribution test systems.
Journal ArticleDOI

Whale optimization algorithm based optimal reactive power dispatch: A case study of the Algerian power system

TL;DR: A new metaheuristic technique inspired from the bubble-net hunting technique of humpback whales, namely whale optimization algorithm (WOA), has been applied to solve the ORPD problem and is compared with two own developed methods.
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