arXiv subjects

Arindam K. Das

Publications and source records attributed to Arindam K. Das.

5 recordsLinked to original sources

arXiv2025

Formulating the Restoration of Distribution Networks as a Multiple Traveling Salesman Problem

Severe weather events can cause extensive damage to electrical distribution networks, requiring a multi-day restoration effort. Optimizing the dispatch of repair crews minimizes the severe socio-economic consequences of such events. Considering both repair times and travel times, we use graphical manipulations to transform this multiple crew scheduling problem into a type of traveling salesman problem(TSP). Specifically, we demonstrate that the restoration problem bears major resemblance to an instance of a cost constrained reward maximizing mTSP (multiple TSP) on node and edge weighted (doubly weighted) graphs (a variant we dub the CCRM-mTSP-DW), where the objective is to maximize the aggregate reward earned during the upcoming restoration window, provided no crew violates its time budget and electrical continuity constraints are met. Despite the rich history of research on the TSP and its variants, this CCRM-mTSP-DW variant has not been studied before, although its closest cousin happens to be the "Selective TSP" (S-TSP). This reinterpretation of the restoration problem not only opens up the possibility of drawing on existing solution methods developed for the TSP and its variants, it also adds a new chapter in the annals of research on "TSP-like'' problems. In this paper, we propose a "TSP-like'' mixed integer linear programming (MILP) model for solving the restoration problem and validate it on the IEEE PES 123-node test feeder network.

eess.SY↗

arXiv2023

Performance Analysis of DNA Crossbar Arrays for High-Density Memory Storage Applications

Deoxyribonucleic acid (DNA) has emerged as a promising building block for next-generation ultra-high density storage devices. Although DNA has high durability and extremely high density in nature, its potential as the basis of storage devices is currently hindered by limitations such as expensive and complex fabrication processes and time-consuming read-write operations. In this article, we propose the use of a DNA crossbar array architecture for an electrically readable Read-Only Memory (DNA-ROM). While information can be written error-free to a DNA-ROM array using appropriate sequence encoding, its read accuracy can be affected by several factors such as array size, interconnect resistance, and Fermi energy deviations from HOMO levels of DNA strands employed in the crossbar. We study the impact of array size and interconnect resistance on the bit error rate of a DNA-ROM array through extensive Monte Carlo simulations. We have also analyzed the performance of our proposed DNA crossbar array for an image storage application, as a function of array size and interconnect resistance. While we expect that future advances in bioengineering and materials science will address some of the fabrication challenges associated with DNA crossbar arrays, we believe that the comprehensive body of results we present in this paper establishes the technical viability of DNA crossbar arrays as low-power, high-density storage devices. Finally, our analysis of array performance vis-a-vis interconnect resistance should provide valuable insights into aspects of the fabrication process such as the proper choice of interconnects necessary for ensuring high read accuracies.

cs.ET↗

arXiv2019

Post-disaster Repair Scheduling in Partially Automated Electricity Distribution Networks

Natural disasters require repairing all damaged components in electricity distribution networks. Optimal scheduling repair crews to minimize the aggregate duration of interruptions reduces the harm. We consider the fact that the number of switches is much smaller than the number of edges. The problem is modeled by a parallel identical machine scheduling with group soft precedence constraints to minimize the total weighted energization time. We propose an LP-based list scheduling algorithm and a conversion algorithm and analyze their theoretical performances.

math.OC↗

arXiv2018

Scheduling Post-Disaster Repairs in Electricity Distribution Networks

Natural disasters, such as hurricanes, earthquakes and large wind or ice storms, typically require the repair of a large number of components in electricity distribution networks. Since power cannot be restored before these repairs have been completed, optimally scheduling the available crews to minimize the cumulative duration of the customer interruptions reduces the harm done to the affected community. Considering the radial network structure of the distribution system, this repair and restoration process can be modeled as a scheduling problem with soft precedence constraints. As a benchmark, we first formulate this problem as a time-indexed ILP with valid inequalities. Three practical methods are then proposed to solve the problem: (i) an LP-based list scheduling algorithm, (ii) a single to multi-crew repair schedule conversion algorithm, and (iii) a dispatch rule based on $ρ$-factors which can be interpreted as Component Importance Measures. We show that the first two algorithms are $2$ and $\left(2 - \frac{1}{m}\right)$ approximations respectively. We also prove that the latter two algorithms are equivalent. Numerical results validate the effectiveness of the proposed methods.

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arXiv2017

Distribution Systems Hardening against Natural Disasters

Distribution systems are often crippled by catastrophic damage caused by a natural disaster. Well-designed hardening can significantly improve the performance of post-disaster restoration operations. Such performance is quantified by a resilience measure associated with the operability trajectory. The distribution system hardening problem can be formulated as a two-stage stochastic problem, where the inner operational problem addresses the proper sequencing of post-disaster repairs and the outer problem the judicious selection of components to harden. We propose a deterministic robust reformulation with two solution methods, an MILP formulation and a heuristic approach. We provide computational evidence on various IEEE test feeders which illustrates that the heuristic approach provides near-optimal hardening solutions efficiently.

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