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Book ; Online ; E-Book: Erneuerbare Energien

Kaltschmitt, Martin / Streicher, Wolfgang / Wiese, Andreas

Systemtechnik · Wirtschaftlichkeit · Umweltaspekte

2020

Abstract: Dieses Standardwerk stellt die physikalisch-technischen Grundlagen und die aktuelle Systemtechnik für Anlagen und Systeme zur Nutzung regenerativer Energien zur Strom- und Wärmebereitstellung dar. Außerdem gibt es einen umfassenden Überblick über die ... ...

Author's details	edited by Martin Kaltschmitt, Wolfgang Streicher, and Andreas Wiese
Abstract	Dieses Standardwerk stellt die physikalisch-technischen Grundlagen und die aktuelle Systemtechnik für Anlagen und Systeme zur Nutzung regenerativer Energien zur Strom- und Wärmebereitstellung dar. Außerdem gibt es einen umfassenden Überblick über die Charakteristik des erneuerbaren Energieangebots. Ausgehend davon werden Kennzahlen für eine ökonomische und ökologische Bewertung zugänglich gemacht; außerdem werden die Potenziale der verschiedenen Optionen zur Nutzung regenerativer Energien und deren derzeitige Nutzung diskutiert. Im Einzelnen werden die folgenden Möglichkeiten zur Nutzung des regenerativen Energieangebots vertieft dargestellt: - passive Solarenergienutzung, - solarthermische Wärmebereitstellung, - photovoltaische Stromerzeugung, - Bereitstellung elektrischer Energie aus Lauf- und Speicherwasserkraft, - Stromerzeugung aus einer Onshore- und Offshore-Windkraftnutzung, - Wärmebereitstellung mithilfe von Wärmepumpen aus Umgebungswärme (d. h. Umgebungsluft und oberflächennaher Erdwärme), - Strom- und Wärmebereitstellung aus der Energie des tiefen Untergrunds. Zusätzlich werden die Möglichkeiten einer Nutzung der Meeresenergien und der solarthermischen Stromerzeugung dargestellt. Außerdem wird auf die Speicherung elektrischer und thermischer Energie sowie auf Strom- und Wärmenetze eingegangen. Nicht diskutiert wird dagegen die Energiegewinnung aus Biomasse. Neben seiner Eignung für die universitäre und außeruniversitäre Lehre bietet das Buch Entscheidungsträgern in Energiewirtschaft, Politik, Verwaltung und Administration sowie Wissenschaftlern und Beratern eine fundierte, verlässliche und hochaktuelle Wissensbasis. Die Herausgeber Prof. Dr.-Ing. Martin Kaltschmitt, Technische Universität Hamburg (TUHH), Institut für Umwelttechnik und Energiewirtschaft (IUE), Hamburg Univ.-Prof. Dipl.-Ing. Dr. Wolfgang Streicher, Universität Innsbruck, Institut für Konstruktion und Materialwissenschaften, Arbeitsbereich Energieeffizientes Bauen, Innsbruck Prof. Dr.-Ing. Andreas Wiese, GOPA International Energy Consultants, Bad Homburg.
Keywords	Renewable energy sources ; Engineering ; Environmental sciences
Subject code	621.042
Language	German
Size	1 online resource (XLV, 1249 S. 664 Abb.)
Edition	Sixth edition.
Publisher	Springer-Verlag GmbH
Publishing place	Berlin, Germany
Document type	Book ; Online ; E-Book
Remark	Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
ISBN	3-662-61190-2 ; 3-662-61189-9 ; 978-3-662-61190-6 ; 978-3-662-61189-0
DOI	10.1007/978-3-662-61190-6
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Book ; Thesis: Inzidenz von Pseudoarthrosen bei geschlossenen Frakturen

Wiese, Andreas

1995

Author's details	vorgelegt von: Andreas Wiese
Language	German
Size	60 Bl. : graph. Darst.
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Hannover, Med. Hochsch., Diss., 1996
HBZ-ID	HT007341980
Database	Catalogue ZB MED Medicine, Health

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Book ; Online: Online and Dynamic Algorithms for Geometric Set Cover and Hitting Set

Khan, Arindam / Lonkar, Aditya / Rahul, Saladi / Subramanian, Aditya / Wiese, Andreas

2023

Abstract: Set cover and hitting set are fundamental problems in combinatorial optimization which are well-studied in the offline, online, and dynamic settings. We study the geometric versions of these problems and present new online and dynamic algorithms for them. ...

Abstract	Set cover and hitting set are fundamental problems in combinatorial optimization which are well-studied in the offline, online, and dynamic settings. We study the geometric versions of these problems and present new online and dynamic algorithms for them. In the online version of set cover (resp. hitting set), $m$ sets (resp.~$n$ points) are give $n$ points (resp.~$m$ sets) arrive online, one-by-one. In the dynamic versions, points (resp. sets) can arrive as well as depart. Our goal is to maintain a set cover (resp. hitting set), minimizing the size of the computed solution. For online set cover for (axis-parallel) squares of arbitrary sizes, we present a tight $O(\log n)$-competitive algorithm. In the same setting for hitting set, we provide a tight $O(\log N)$-competitive algorithm, assuming that all points have integral coordinates in $[0,N)^{2}$. No online algorithm had been known for either of these settings, not even for unit squares (apart from the known online algorithms for arbitrary set systems). For both dynamic set cover and hitting set with $d$-dimensional hyperrectangles, we obtain $(\log m)^{O(d)}$-approximation algorithms with $(\log m)^{O(d)}$ worst-case update time. This partially answers an open question posed by Chan et al. [SODA'22]. Previously, no dynamic algorithms with polylogarithmic update time were known even in the setting of squares (for either of these problems). Our main technical contributions are an \emph{extended quad-tree }approach and a \emph{frequency reduction} technique that reduces geometric set cover instances to instances of general set cover with bounded frequency.
Keywords	Computer Science - Computational Geometry ; Computer Science - Data Structures and Algorithms
Subject code	005
Publishing date	2023-03-16
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A $(3+\epsilon)$-approximation algorithm for the minimum sum of radii problem with outliers and extensions for generalized lower bounds

Buchem, Moritz / Ettmayr, Katja / Rosado, Hugo Kooki Kasuya / Wiese, Andreas

2023

Abstract: For a given set of points in a metric space and an integer $k$, we seek to partition the given points into $k$ clusters. For each computed cluster, one typically defines one point as the center of the cluster. A natural objective is to minimize the sum ... ...

Abstract	For a given set of points in a metric space and an integer $k$, we seek to partition the given points into $k$ clusters. For each computed cluster, one typically defines one point as the center of the cluster. A natural objective is to minimize the sum of the cluster center's radii, where we assign the smallest radius $r$ to each center such that each point in the cluster is at a distance of at most $r$ from the center. The best-known polynomial time approximation ratio for this problem is $3.389$. In the setting with outliers, i.e., we are given an integer $m$ and allow up to $m$ points that are not in any cluster, the best-known approximation factor is $12.365$. In this paper, we improve both approximation ratios to $3+\epsilon$. Our algorithms are primal-dual algorithms that use fundamentally new ideas to compute solutions and to guarantee the claimed approximation ratios. For example, we replace the classical binary search to find the best value of a Lagrangian multiplier $\lambda$ by a primal-dual routine in which $\lambda$ is a variable that is raised. Also, we show that for each connected component due to almost tight dual constraints, we can find one single cluster that covers all its points and we bound its cost via a new primal-dual analysis. We remark that our approximation factor of $3+\epsilon$ is a natural limit for the known approaches in the literature. Then, we extend our results to the setting of lower bounds. There are algorithms known for the case that for each point $i$ there is a lower bound $L_{i}$, stating that we need to assign at least $L_{i}$ clients to $i$ if $i$ is a cluster center. For this setting, there is a $ 3.83$ approximation if outliers are not allowed and a ${12.365}$-approximation with outliers. We improve both ratios to $3.5 + \epsilon$ and, at the same time, generalize the type of allowed lower bounds.
Keywords	Computer Science - Data Structures and Algorithms ; Computer Science - Computational Geometry
Publishing date	2023-11-10
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A PTAS for Minimizing Weighted Flow Time on a Single Machine

Armbruster, Alexander / Rohwedder, Lars / Wiese, Andreas

2022

Abstract: An important objective in scheduling literature is to minimize the sum of weighted flow times. We are given a set of jobs where each job is characterized by a release time, a processing time, and a weight. Our goal is to find a preemptive schedule on a ... ...

Abstract	An important objective in scheduling literature is to minimize the sum of weighted flow times. We are given a set of jobs where each job is characterized by a release time, a processing time, and a weight. Our goal is to find a preemptive schedule on a single machine that minimizes the sum of the weighted flow times of the jobs, where the flow time of a job is the time between its completion time and its release time. The currently best known polynomial time algorithm for the problem is a (2+eps)-approximation by Rohwedder and Wiese [STOC 2021] which builds on the prior break-through result by Batra, Garg, and Kumar [FOCS 2018] who found the first pseudo-polynomial time constant factor approximation algorithm for the problem, and on the result by Feige, Kulkarni, and Li [SODA 2019] who turned the latter into a polynomial time algorithm. However, it remains open whether the problem admits a PTAS. We answer this question in the affirmative and present a polynomial time (1+eps)-approximation algorithm for weighted flow time on a single machine. We rely on a reduction of the problem to a geometric covering problem, which was introduced in the mentioned (2+eps)-approximation algorithm, losing a factor 1+eps in the approximation ratio. However, unlike that algorithm, we solve the resulting instances of this problem exactly, rather than losing a factor 2+eps. Key for this is to identify and exploit structural properties of instances of the geometric covering problem which arise in the reduction from weighted flow time.
Keywords	Computer Science - Data Structures and Algorithms
Subject code	511
Publishing date	2022-08-05
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: On the Two-Dimensional Knapsack Problem for Convex Polygons

Merino, Arturo / Wiese, Andreas

2020

Abstract: We study the two-dimensional geometric knapsack problem for convex polygons. Given a set of weighted convex polygons and a square knapsack, the goal is to select the most profitable subset of the given polygons that fits non-overlappingly into the ... ...

Abstract	We study the two-dimensional geometric knapsack problem for convex polygons. Given a set of weighted convex polygons and a square knapsack, the goal is to select the most profitable subset of the given polygons that fits non-overlappingly into the knapsack. We allow to rotate the polygons by arbitrary angles. We present a quasi-polynomial time $O(1)$-approximation algorithm for the general case and a polynomial time $O(1)$-approximation algorithm if all input polygons are triangles, both assuming polynomially bounded integral input data. Also, we give a quasi-polynomial time algorithm that computes a solution of optimal weight under resource augmentation, i.e., we allow to increase the size of the knapsack by a factor of $1+\delta$ for some $\delta>0$ but compare ourselves with the optimal solution for the original knapsack. To the best of our knowledge, these are the first results for two-dimensional geometric knapsack in which the input objects are more general than axis-parallel rectangles or circles and in which the input polygons can be rotated by arbitrary angles. Comment: 32 pages, 7 figures. A preliminary version appears in ICALP 2020
Keywords	Computer Science - Data Structures and Algorithms ; Computer Science - Computational Geometry
Subject code	511
Publishing date	2020-07-31
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: A $(2+\varepsilon)$-approximation algorithm for preemptive weighted flow time on a single machine

Rohwedder, Lars / Wiese, Andreas

2020

Abstract: Weighted flow time is a fundamental and very well-studied objective function in scheduling. In this paper, we study the setting of a single machine with preemptions. The input consists of a set of jobs, characterized by their processing times, release ... ...

Abstract	Weighted flow time is a fundamental and very well-studied objective function in scheduling. In this paper, we study the setting of a single machine with preemptions. The input consists of a set of jobs, characterized by their processing times, release times, and weights and we want to compute a (possibly preemptive) schedule for them. The objective is to minimize the sum of the weighted flow times of the jobs, where the flow time of a job is the time between its release date and its completion time. It had been a long-standing open problem to find a polynomial time $O(1)$-approximation algorithm for this setting. In a recent break-through result, Batra, Garg, and Kumar (FOCS 2018) found such an algorithm if the input data are polynomially bounded integers, and Feige, Kulkarni, and Li (SODA 2019) presented a black-box reduction to this setting. The resulting approximation ratio is a (not explicitly stated) constant which is at least $10.000$. In this paper we improve this ratio to $2+\varepsilon$. The algorithm by Batra, Garg, and Kumar (FOCS 2018) reduces the problem to Demand MultiCut on trees and solves the resulting instances via LP-rounding and a dynamic program. Instead, we first reduce the problem to a (different) geometric problem while losing only a factor $1+\epsilon$, and then solve its resulting instances up to a factor of $2+\epsilon$ by a dynamic program. In particular, our reduction ensures certain structural properties, thanks to which we do not need LP-rounding methods. We believe that our result makes substantial progress towards finding a PTAS for weighted flow time on a single machine.
Keywords	Computer Science - Data Structures and Algorithms
Subject code	511
Publishing date	2020-11-11
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Tight Approximation Algorithms for Two Dimensional Guillotine Strip Packing

Khan, Arindam / Lonkar, Aditya / Maiti, Arnab / Sharma, Amatya / Wiese, Andreas

2022

Abstract: In the Strip Packing problem (SP), we are given a vertical half-strip $[0,W]\times[0,\infty)$ and a set of $n$ axis-aligned rectangles of width at most $W$. The goal is to find a non-overlapping packing of all rectangles into the strip such that the ... ...

Abstract	In the Strip Packing problem (SP), we are given a vertical half-strip $[0,W]\times[0,\infty)$ and a set of $n$ axis-aligned rectangles of width at most $W$. The goal is to find a non-overlapping packing of all rectangles into the strip such that the height of the packing is minimized. A well-studied and frequently used practical constraint is to allow only those packings that are guillotine separable, i.e., every rectangle in the packing can be obtained by recursively applying a sequence of edge-to-edge axis-parallel cuts (guillotine cuts) that do not intersect any item of the solution. In this paper, we study approximation algorithms for the Guillotine Strip Packing problem (GSP), i.e., the Strip Packing problem where we require additionally that the packing needs to be guillotine separable. This problem generalizes the classical Bin Packing problem and also makespan minimization on identical machines, and thus it is already strongly NP-hard. Moreover, due to a reduction from the Partition problem, it is NP-hard to obtain a polynomial-time $(3/2-\varepsilon)$-approximation algorithm for GSP for any $\varepsilon>0$ (exactly as Strip Packing). We provide a matching polynomial time $(3/2+\varepsilon)$-approximation algorithm for GSP. Furthermore, we present a pseudo-polynomial time $(1+\varepsilon)$-approximation algorithm for GSP. This is surprising as it is NP-hard to obtain a $(5/4-\varepsilon)$-approximation algorithm for (general) Strip Packing in pseudo-polynomial time. Thus, our results essentially settle the approximability of GSP for both the polynomial and the pseudo-polynomial settings. Comment: 32 pages, 9 figures
Keywords	Computer Science - Data Structures and Algorithms ; Computer Science - Computational Geometry ; F.2.2
Subject code	000 ; 518
Publishing date	2022-02-12
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Breaking the Barrier of 2 for the Storage Allocation Problem

Mömke, Tobias / Wiese, Andreas

2019

Abstract: Packing problems are an important class of optimization problems. The probably most well-known problem if this type is knapsack and many generalizations of it have been studied in the literature like Two-dimensional Geometric Knapsack (2DKP) and ... ...

Abstract	Packing problems are an important class of optimization problems. The probably most well-known problem if this type is knapsack and many generalizations of it have been studied in the literature like Two-dimensional Geometric Knapsack (2DKP) and Unsplittable Flow on a Path (UFP). For the latter two problems, recently the first polynomial time approximation algorithms with better approximation ratios than 2 were presented [G\'alvez et al., FOCS 2017][Grandoni et al., STOC 2018]. In this paper we break the barrier of 2 for the Storage Allocation Problem (SAP) which is a natural intermediate problem between 2DKP and UFP. We are given a path with capacitated edges and a set of tasks where each task has a start vertex, an end vertex, a size, and a profit. We seek to select the most profitable set of tasks that we can draw as non-overlapping rectangles underneath the capacity profile of the edges where the height of each rectangle equals the size of the corresponding task. This problem is motivated by settings of allocation resources like memory, bandwidths, etc. where each request needs a contiguous portion of the resource. The best known polynomial time approximation algorithm for SAP has an approximation ratio of 2+epsilon$ [M\"omke and Wiese, ICALP 2015] and no better quasi-polynomial time algorithm is known. We present a polynomial time (63/32) < 1.969-approximation algorithm for the case of uniform edge capacities and a quasi-polynomial time (1.997)-approximation algorithm for non-uniform quasi-polynomially bounded edge capacities. Finally, we show that under slight resource augmentation we can obtain approximation ratios of 3/2 + epsilon in polynomial time and 1 + epsilon in quasi-polynomial time, both for arbitrary edge capacities. Comment: 54 pages, 10 figures
Keywords	Computer Science - Data Structures and Algorithms ; Computer Science - Discrete Mathematics ; 68W25 ; I.2.8 ; F.2.2 ; G.1.2
Subject code	518
Publishing date	2019-11-25
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: On Guillotine Separable Packings for the Two-dimensional Geometric Knapsack Problem

Khan, Arindam / Maiti, Arnab / Sharma, Amatya / Wiese, Andreas

2021

Abstract: In two-dimensional geometric knapsack problem, we are given a set of n axis-aligned rectangular items and an axis-aligned square-shaped knapsack. Each item has integral width, integral height and an associated integral profit. The goal is to find a (non- ... ...

Abstract	In two-dimensional geometric knapsack problem, we are given a set of n axis-aligned rectangular items and an axis-aligned square-shaped knapsack. Each item has integral width, integral height and an associated integral profit. The goal is to find a (non-overlapping axis-aligned) packing of a maximum profit subset of rectangles into the knapsack. A well-studied and frequently used constraint in practice is to allow only packings that are guillotine separable, i.e., every rectangle in the packing can be obtained by recursively applying a sequence of edge-to-edge axis-parallel cuts that do not intersect any item of the solution. In this paper we study approximation algorithms for the geometric knapsack problem under guillotine cut constraints. We present polynomial time (1 + {\epsilon})-approximation algorithms for the cases with and without allowing rotations by 90 degrees, assuming that all input numeric data are polynomially bounded in n. In comparison, the best-known approximation factor for this setting is 3 + {\epsilon} [Jansen-Zhang, SODA 2004], even in the cardinality case where all items have the same profit. Our main technical contribution is a structural lemma which shows that any guillotine packing can be converted into another structured guillotine packing with almost the same profit. In this packing, each item is completely contained in one of a constant number of boxes and L-shaped regions, inside which the items are placed by a simple greedy routine. In particular, we provide a clean sufficient condition when such a packing obeys the guillotine cut constraints which might be useful for other settings where these constraints are imposed. Comment: 39 pages, 13 figures, To appear in SOCG 2021
Keywords	Computer Science - Data Structures and Algorithms ; Computer Science - Computational Geometry ; 68W25
Subject code	000
Publishing date	2021-03-17
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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