Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such ...problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution.
This book is the latest update of the very highly-regarded PHP Objects, Patterns, and Practice, a book that many PHP developers find invaluable. It explains PHP's object-oriented features and object ...tools in detail, and then goes on to explain how to use enterprise design patterns for more effective and efficient development. It also covers useful development tools such as SVN, PEAR, and phpDocumentor. In short, it's a book that every PHP developer must have.
A parallel automated resilience-based restoration methodology is presented in the power system to minimize impact due to emergency power outages. In this power restoration process, a black start unit ...is assigned to a small region (i.e., a section) on an as-needed basis. A mixed integer nonlinear programming model is developed in order to optimally sectionalize the region of interest all the while maximizing the resiliency in terms of load shedding, restoration time, and network connectivity. For solving this large scale optimization model, a bi-level programming approach is proposed. This approach consists of two optimization levels. The sectionalization problem (upper level) is a mixed integer programming model and finds the optimal section set. The restoration problem (lower level) is a linear model and determines the dc optimal power flow and restoration time for the optimal section set identified in the upper level. We use the pre-emptive method of goal programming to deal with multiple conflicting objectives in the model. Our proposed solution approach outperformed mathematical programming with equilibrium constraints and found near optimal solutions. Numerical results and sensitivity analysis from two case studies (6- and 118-bus IEEE test systems) are further discussed to demonstrate the efficiency of the solution approach.
A multitude of different probabilistic programming languages exists today, all extending a traditional programming language with primitives to support modeling of complex, structured probability ...distributions. Each of these languages employs its own probabilistic primitives, and comes with a particular syntax, semantics and inference procedure. This makes it hard to understand the underlying programming concepts and appreciate the differences between the different languages. To obtain a better understanding of probabilistic programming, we identify a number of core programming concepts underlying the primitives used by various probabilistic languages, discuss the execution mechanisms that they require and use these to position and survey state-of-the-art probabilistic languages and their implementation. While doing so, we focus on probabilistic extensions of
logic
programming languages such as Prolog, which have been considered for over 20 years.
Successful transition to active distribution networks (ADNs) requires a planning methodology that includes an accurate network model and accounts for the major sources of uncertainty. Considering ...these two essential features, this paper proposes a novel model for the multistage distribution expansion planning (MDEP) problem, which is able to jointly expand both the network assets (feeders and substations) and renewable/conventional distributed generators. With respect to network characteristics, the proposed planning model employs a convex conic quadratic format of ac power flow equations that is linearized using a highly accurate polyhedral-based linearization method. Furthermore, a chance-constrained programming approach is utilized to deal with the uncertain renewables and loads. In this regard, as the probability distribution functions of uncertain parameters are not perfectly known, a distributionally robust (DR) reformulation is proposed for the chance constraints that guarantees the robustness of the expansion plans against all uncertainty distributions defined within a moment-based ambiguity set. Effective linearization techniques are also devised to eliminate the nonlinearities of the proposed DR reformulation, which yields a distributionally robust chance-constrained mixed-integer linear programming model for the MDEP problem of ADNs. Finally, the 24-node and 138-node test systems are used to demonstrate the effectiveness of the proposed planning methodology.
In this paper we discuss statistical properties and convergence of the Stochastic Dual Dynamic Programming (SDDP) method applied to multistage linear stochastic programming problems. We assume that ...the underline data process is stagewise independent and consider the framework where at first a random sample from the original (true) distribution is generated and consequently the SDDP algorithm is applied to the constructed Sample Average Approximation (SAA) problem. Then we proceed to analysis of the SDDP solutions of the SAA problem and their relations to solutions of the “true” problem. Finally we discuss an extension of the SDDP method to a risk averse formulation of multistage stochastic programs. We argue that the computational complexity of the corresponding SDDP algorithm is almost the same as in the risk neutral case.
Nominal Sets Pitts, Andrew M.
05/2013, Letnik:
v.Series Number 57
eBook
Nominal sets provide a promising new mathematical analysis of names in formal languages based upon symmetry, with many applications to the syntax and semantics of programming language constructs that ...involve binding, or localising names. Part I provides an introduction to the basic theory of nominal sets. In Part II, the author surveys some of the applications that have developed in programming language semantics (both operational and denotational), functional programming and logic programming. As the first book to give a detailed account of the theory of nominal sets, it will be welcomed by researchers and graduate students in theoretical computer science.
This open access book is a modern guide for all C++ programmers to learn Threading Building Blocks (TBB). Written by TBB and parallel programming experts, this book reflects their collective decades ...of experience in developing and teaching parallel programming with TBB, offering their insights in an approachable manner. Throughout the book the authors present numerous examples and best practices to help you become an effective TBB programmer and leverage the power of parallel systems. Pro TBB starts with the basics, explaining parallel algorithms and C++'s built-in standard template library for parallelism. You'll learn the key concepts of managing memory, working with data structures and how to handle typical issues with synchronization. Later chapters apply these ideas to complex systems to explain performance tradeoffs, mapping common parallel patterns, controlling threads and overhead, and extending TBB to program heterogeneous systems or system-on-chips. What You'll Learn Use Threading Building Blocks to produce code that is portable, simple, scalable, and more understandable Review best practices for parallelizing computationally intensive tasks in your applications Integrate TBB with other threading packages Create scalable, high performance data-parallel programs Work with generic programming to write efficient algorithms Who This Book Is For C++ programmers learning to run applications on multicore systems, as well as C or C++ programmers without much experience with templates. No previous experience with parallel programming or multicore processors is required. ;
This open access book constitutes the proceedings of the 23rd International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2020, which took place in Dublin, ...Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The 31 regular papers presented in this volume were carefully reviewed and selected from 98 submissions. The papers cover topics such as categorical models and logics; language theory, automata, and games; modal, spatial, and temporal logics; type theory and proof theory; concurrency theory and process calculi; rewriting theory; semantics of programming languages; program analysis, correctness, transformation, and verification; logics of programming; software specification and refinement; models of concurrent, reactive, stochastic, distributed, hybrid, and mobile systems; emerging models of computation; logical aspects of computational complexity; models of software security; and logical foundations of data bases.?
This book takes a single line of code--the extremely concise BASIC program for the Commodore 64 inscribed in the title--and uses it as a lens through which to consider the phenomenon of creative ...computing and the way computer programs exist in culture. The authors of this collaboratively written book treat code not as merely functional but as a text--in the case of 10 PRINT, a text that appeared in many different printed sources--that yields a story about its making, its purpose, its assumptions, and more. They consider randomness and regularity in computing and art, the maze in culture, the popular BASIC programming language, and the highly influential Commodore 64 computer.
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