427 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Serial-batch scheduling – the special case of laser-cutting machines
The dissertation deals with a problem in the field of short-term production planning, namely the scheduling of laser-cutting machines. The object of decision is the grouping of production orders (batching) and the sequencing of these order groups on one or more machines (scheduling). This problem is also known in the literature as "batch scheduling problem" and belongs to the class of combinatorial optimization problems due to the interdependencies between the batching and the scheduling decisions. The concepts and methods used are mainly from production planning, operations research and machine learning
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Non-economic objectives, globalisation and multilateral trade cooperation
Global trade and investment are increasingly affected by unilateral policies motivated by both economic and noneconomic objectives such as safeguarding national and economic security, combatting climate change, and promoting social values. Many of the associated interventions target the global value chains that have been a driver of globalisation. Taken together, the rise in unilateralism increases policy uncertainty and associated risk premia, distorts trade and investment decisions, and adversely affects prospects for developing countries to attain sustainable development goals. This new study summarises extant multilateral disciplines on use of trade policies motivated by noneconomic objectives, documents the rising use of such measures and presents pragmatic suggestions to sustain multilateral trade cooperation in a world characterised by rising geopolitical and geo-economic rivalry and existential threats.-- 1. National security and other non‑economic objectives -- 2. Economic and non-economic objectives -- 3. The increasing use of trade policy for non-economic objectives -- 4. International disciplines on the use of trade for non-economic objectives -- 5. National security practice in the GATT period (1948-94) -- 6. National security in the post-1995 WTO era -- 7. Potential WTO reforms -- 8. Clubs -- 9. Conclusion -- Annexe
Technology Assessment in a Globalized World
This open access book explores the relevance of the concept of technology assessment (TA) on an international and global level. Technologies play a key role in addressing global challenges such as climate change, population aging, digitization, and health. At the same time, their use increases the need for coordinated action and governance at the global level in the field of science, technology and innovation (STI). Featuring case studies on STI fields such as energy, biotechnology, artificial intelligence, and health technology, as well as TA activities at the national and international levels, this book reflects on the challenges and opportunities of global technology governance. It also provides an in-depth discussion of current governmental STI cultures and systems, societal expectations, and the policy priorities needed to achieve coordinated and effective STI intervention in policymaking and public debate at the global level. Lastly, the book promotes the establishment of a forum for a truly global dialogue of TA practitioners, fostering the articulation of their needs, knowledge and perspectives
Operational Research: methods and applications
This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThroughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes
Feebly Interacting Particles: FIPs 2022 workshop report
Particle physics today faces the challenge of explaining the mystery of dark matter, the origin of matter over anti-matter in the Universe, the origin of the neutrino masses, the apparent fine-tuning of the electro-weak scale, and many other aspects of fundamental physics. Perhaps the most striking frontier to emerge in the search for answers involves new physics at mass scales comparable to familiar matter, below the GeV-scale, or even radically below, down to sub-eV scales, and with very feeble interaction strength. New theoretical ideas to address dark matter and other fundamental questions predict such feebly interacting particles (FIPs) at these scales, and indeed, existing data provide numerous hints for such possibility. A vibrant experimental program to discover such physics is under way, guided by a systematic theoretical approach firmly grounded on the underlying principles of the Standard Model. This document represents the report of the FIPs 2022 workshop, held at CERN between the 17 and 21 October 2022 and aims to give an overview of these efforts, their motivations, and the decadal goals that animate the community involved in the search for FIPs
Finding Optimal Diverse Feature Sets with Alternative Feature Selection
Feature selection is popular for obtaining small, interpretable, yet highly
accurate prediction models. Conventional feature-selection methods typically
yield one feature set only, which might not suffice in some scenarios. For
example, users might be interested in finding alternative feature sets with
similar prediction quality, offering different explanations of the data. In
this article, we introduce alternative feature selection and formalize it as an
optimization problem. In particular, we define alternatives via constraints and
enable users to control the number and dissimilarity of alternatives. Next, we
analyze the complexity of this optimization problem and show NP-hardness.
Further, we discuss how to integrate conventional feature-selection methods as
objectives. Finally, we evaluate alternative feature selection with 30
classification datasets. We observe that alternative feature sets may indeed
have high prediction quality, and we analyze several factors influencing this
outcome
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