Non-destructive diagnosis of wiring networks using time domain reflectometry and an improved black hole algorithm

Smail, Mostafa Kamel; Bouchekara, Houssem R. E. H.; Pichon, Lionel; Boudjefdjouf, Hamza; Amloune, Ali; Lacheheb, Z.

doi:10.1080/10589759.2016.1200576

Cited by 15 publications

(8 citation statements)

References 12 publications

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“…The process of computing voltages and currents at the grid cells is repeated until convergence, according to the progress of the optimisation algorithm. More details about using FDTD method used for the diagnosis of wiring networks are given in [21][22][23][24][25][26][27]. Discretisation consumes computer memory, and solving the equations takes significant CPU time and slows the process dramatically.…”

Section: Fdtd Methodsmentioning

confidence: 99%

“…The applied approach for the diagnosis of wiring networks used in this paper is similar to the one that have been developed and applied in [21][22][23][24][25][26][27]. First, a direct (or forward) model based on solving the transmission line telegrapher equations is developed in order to generate TDR responses for a given network.…”

Section: Wire Fault Diagnosis Approachmentioning

confidence: 99%

“…An alternative approach is to use a direct model in an iterative procedure and to minimise the difference between the simulated response and the measured one. The optimisation techniques that can be used are various [21][22][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Performance improvements of wire fault diagnosis approach based on time‐domain reflectometry

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Boudjefdjouf

Bouchekara

et al. 2017

IET Science, Measurement & Technology

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Section: Fdtd Methodsmentioning

confidence: 99%

Section: Wire Fault Diagnosis Approachmentioning

confidence: 99%

See 1 more Smart Citation

Performance improvements of wire fault diagnosis approach based on time‐domain reflectometry

Paulis

Boudjefdjouf

Bouchekara

et al. 2017

IET Science, Measurement & Technology

View full text Add to dashboard Cite

“…Black hole optimization (BHO) can be used to solve binary [72,73], hybrid binary [74], discrete [75], and real problems [63]. The black hole algorithms can solve different NP-hard optimization problems related to electric power systems [76], scheduling in automotive industry [77], pattern synthesis ion radio science [78], earth sciences [79] logistics and supply chain [80], nondestructive testing of wiring networks [81], and electrochemical machining [82].…”

Section: Black Hole Algorithm-based Optimizationmentioning

confidence: 99%

Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Bányai

2018

Energies

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Energy efficiency and environmental issues have been largely neglected in logistics. In a traditional supply chain, the objective of improving energy efficiency is targeted at the level of single parts of the value making chain. Industry 4.0 technologies make it possible to build hyperconnected logistic solutions, where the objective of decreasing energy consumption and economic footprint is targeted at the global level. The problems of energy efficiency are especially relevant in first mile and last mile delivery logistics, where deliveries are composed of individual orders and each order must be picked up and delivered at different locations. Within the frame of this paper, the author describes a real-time scheduling optimization model focusing on energy efficiency of the operation. After a systematic literature review, this paper introduces a mathematical model of last mile delivery problems including scheduling and assignment problems. The objective of the model is to determine the optimal assignment and scheduling for each order so as to minimize energy consumption, which allows to improve energy efficiency. Next, a black hole optimization-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase energy efficiency in last mile logistics.

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“…A continuous black hole algorithm is used to investigate the critical slip surface of soil slope [45] and to support the nondestructive diagnosis of wiring networks. In this research, the combination of BHA and time domain reflectometry shows that BHA can be implemented in real-world systems [46]. BHO can be combined with other heuristic algorithms to improve its efficiency and convergence.…”

Section: Literature Reviewmentioning

confidence: 99%

Smart Scheduling: An Integrated First Mile and Last Mile Supply Approach

2018

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Supply chain management applies more and more Industry 4.0 innovations to increase their availability, elasticity, sustainability, and efficiency. In interconnected logistics networks, operations are integrated from suppliers through 3rd party logistics providers to customers. There are different delivery models depending on the time and cost. In the last few years, a wide range of customers is willing to pay an extra fee for the same delivery or instant delivery. This fact led to the increased importance of the optimized design and control of first mile/last mile (FMLM) delivery solutions. Cyberphysical system-based service innovations make it possible to enhance the productivity of FMLM delivery in the big data environment. The design and operation problems can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on heuristic and metaheuristic algorithms. This research proposes an integrated supply model of FMLM delivery. After a careful literature review, this paper introduces a mathematical model to formulate the problem of realtime smart scheduling of FMLM delivery. The integrated model includes the assignment of first mile and last mile delivery tasks to the available resources and the optimization of operations costs, while constraints like capacity, time window, and availability are taken into consideration. Next, a black hole optimization-(BHO-) based algorithm dealing with a multiobjective supply chain model is presented. The sensitivity of the enhanced algorithm is tested with benchmark functions. Numerical results with different datasets demonstrate the efficiency of the proposed model and validate the usage of Industry 4.0 inventions in FMLM delivery.

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Non-destructive diagnosis of wiring networks using time domain reflectometry and an improved black hole algorithm

Abstract: International audienc

Cited by 15 publications

References 12 publications

Performance improvements of wire fault diagnosis approach based on time‐domain reflectometry

Performance improvements of wire fault diagnosis approach based on time‐domain reflectometry

Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Smart Scheduling: An Integrated First Mile and Last Mile Supply Approach

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