10,311 research outputs found
A Multi-objective Perspective for Operator Scheduling using Fine-grained DVS Architecture
The stringent power budget of fine grained power managed digital integrated
circuits have driven chip designers to optimize power at the cost of area and
delay, which were the traditional cost criteria for circuit optimization. The
emerging scenario motivates us to revisit the classical operator scheduling
problem under the availability of DVFS enabled functional units that can
trade-off cycles with power. We study the design space defined due to this
trade-off and present a branch-and-bound(B/B) algorithm to explore this state
space and report the pareto-optimal front with respect to area and power. The
scheduling also aims at maximum resource sharing and is able to attain
sufficient area and power gains for complex benchmarks when timing constraints
are relaxed by sufficient amount. Experimental results show that the algorithm
that operates without any user constraint(area/power) is able to solve the
problem for most available benchmarks, and the use of power budget or area
budget constraints leads to significant performance gain.Comment: 18 pages, 6 figures, International journal of VLSI design &
Communication Systems (VLSICS
Efficient energy management for the internet of things in smart cities
The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities
Human-Machine Collaborative Optimization via Apprenticeship Scheduling
Coordinating agents to complete a set of tasks with intercoupled temporal and
resource constraints is computationally challenging, yet human domain experts
can solve these difficult scheduling problems using paradigms learned through
years of apprenticeship. A process for manually codifying this domain knowledge
within a computational framework is necessary to scale beyond the
``single-expert, single-trainee" apprenticeship model. However, human domain
experts often have difficulty describing their decision-making processes,
causing the codification of this knowledge to become laborious. We propose a
new approach for capturing domain-expert heuristics through a pairwise ranking
formulation. Our approach is model-free and does not require enumerating or
iterating through a large state space. We empirically demonstrate that this
approach accurately learns multifaceted heuristics on a synthetic data set
incorporating job-shop scheduling and vehicle routing problems, as well as on
two real-world data sets consisting of demonstrations of experts solving a
weapon-to-target assignment problem and a hospital resource allocation problem.
We also demonstrate that policies learned from human scheduling demonstration
via apprenticeship learning can substantially improve the efficiency of a
branch-and-bound search for an optimal schedule. We employ this human-machine
collaborative optimization technique on a variant of the weapon-to-target
assignment problem. We demonstrate that this technique generates solutions
substantially superior to those produced by human domain experts at a rate up
to 9.5 times faster than an optimization approach and can be applied to
optimally solve problems twice as complex as those solved by a human
demonstrator.Comment: Portions of this paper were published in the Proceedings of the
International Joint Conference on Artificial Intelligence (IJCAI) in 2016 and
in the Proceedings of Robotics: Science and Systems (RSS) in 2016. The paper
consists of 50 pages with 11 figures and 4 table
Bütünleşik tedarik zinciri çizelgeleme modelleri: Bir literatür taraması
Research on integration of supply chain and scheduling is relatively recent, and
number of studies on this topic is increasing. This study provides a comprehensive
literature survey about Integrated Supply Chain Scheduling (ISCS) models to help
identify deficiencies in this area. For this purpose, it is thought that this study will
contribute in terms of guiding researchers working in this field. In this study,
existing literature on ISCS problems are reviewed and summarized by introducing
the new classification scheme. The studies were categorized by considering the
features such as the number of customers (single or multiple), product lifespan
(limited or unlimited), order sizes (equal or general), vehicle characteristics
(limited/sufficient and homogeneous/heterogeneous), machine configurations and
number of objective function (single or multi objective). In addition, properties of
mathematical models applied for problems and solution approaches are also
discussed.Bütünleşik Tedarik Zinciri Çizelgeleme (BTZÇ) üzerine yapılan araştırmalar
nispeten yenidir ve bu konu üzerine yapılan çalışma sayısı artmaktadır. Bu çalışma,
bu alandaki eksiklikleri tespit etmeye yardımcı olmak için BTZÇ modelleri hakkında
kapsamlı bir literatür araştırması sunmaktadır. Bu amaçla, bu çalışmanın bu alanda
çalışan araştırmacılara rehberlik etmesi açısından katkı sağlayacağı
düşünülmektedir. Bu çalışmada, BTZÇ problemleri üzerine mevcut literatür gözden
geçirilmiş ve yeni sınıflandırma şeması tanıtılarak çalışmalar özetlenmiştir.
Çalışmalar; tek veya çoklu müşteri sayısı, sipariş büyüklüğü tipi (eşit veya genel),
ürün ömrü (sınırlı veya sınırsız), araç karakteristikleri (sınırlı/yeterli ve
homojen/heterojen), makine konfigürasyonları ve amaç fonksiyonu sayısı (tek veya
çok amaçlı) gibi özellikler dikkate alınarak kategorize edildi. Ayrıca problemler için
uygulanan matematiksel modellerin özellikleri ve çözüm yaklaşımları da
tartışılmıştır
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