Bi-level problem as a plain multi-objective optimization problem: A preliminary study

Dutta, Pooja; Datta, Dilip

doi:10.1109/amiams.2017.8069191

Cited by 1 publication

(2 citation statements)

References 23 publications

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“…In addition, electromagnetic wave power density for embedded systems can be evaluated with the sum of the number of embedded systems as follows. j S j (12) where j represents the number of embedded systems in direct effect. Figure 9d demonstrates the semidirect effect that was located in the neighborhood of the direct effect.…”

Section: N Shape With Door Layoutmentioning

confidence: 99%

“…It was used to solve the disc brake and weld beam design problems. As a problem from multiple object functions evolves to multiple levels, Dutta and Datta [12] applied a combine-and-transform method to combine both levels of a multiobjective optimization problem to a single level. Zhou [13] presented a decomposition-based multiobjective tabu search algorithm for multiobjective unconstrained binary quadratic programming problems.…”

Section: Introductionmentioning

confidence: 99%

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Multiple-Embedded-System Optimization Layout for Electromagnetic Wave Power Density in Complex Environments

Fan

2020

Energies

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Many embedded systems are implemented for healthcare, and smart homes and spaces. These devices are generally designed for elderly care, for monitoring, surveillance, and collection information. As embedded systems are ubiquitous and pervasive in a smart home, office, or space, different layout affects not only reduce the implementation cost but also the power density of electromagnetic waves. This study aimed to develop a multiple-embedded-system optimization layout to consume less electromagnetic wave power density and gain better communication strength. For smart offices, we analyzed the layout topology of n-shaped and n-shaped with door layout categories. On the basis of the location of each embedded system in a communication center via an n-shaped layout, we investigated the electromagnetic wave effect to the local, direct, and semidirect effects. Indirect and subindirect effects were also studied in the n-shaped layout with a door. In addition, we derived a set of formulas from the scope for the diverse effects to help users to quickly identify the scope of each effect. To verify the multiple-embedded-system optimization layout, 16 cooperating embedded systems with four test cases in a smart office were used to evaluate the diverse effects of electromagnetic wave power density and communication strength. Experiment results showed that the optimization layout consumed 3950 × 10−6 W/m2 electromagnetic wave power density.

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Section: N Shape With Door Layoutmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%