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Computer Science (R0)

Stanislaw Gawiejnowicz

Models and Algorithms of Time-Dependent Scheduling

&lt;p&gt;Part I, Fundamentals.- Fundamentals.- Preliminaries.- Problems and Algorithms.- NP-Complete Problems.- Part II, Scheduling Models.- The Classical Scheduling Theory.- The Modern Scheduling Theory.- The Time-Dependent Scheduling.- Part III, Polynomial Problems.- Polynomial Single Machine Problems.- Polynomial Parallel Machine Problems.- Polynomial Dedicated Machine Problems.- Part IV, NP-Hard Problems.- NP-Hard Single Machine Problems.- NP-Hard Parallel Machine Problems.- NP-Hard Dedicated Machine Problems.- Part V, Algorithms.- Exact Algorithms.- Approximation Algorithms and Schemes.- Greedy Algorithms Based on Signatures.- Heuristic Algorithms.- Local Search and Meta-heuristic Algorithms.- Part VI, Advanced Topics.- Time-Dependent Scheduling Under Precedence Constraints.- Matrix Methods in Time-Dependent Scheduling.- Bi-criteria Time-Dependent Scheduling.- New Topics in Time-Dependent Scheduling.- App. A, Open Time-Dependent Scheduling Problems.- List of Algorithms.- List of Figures.- List of Tables.- Symbol Index.- Subject Index.&lt;br&gt;&lt;/p&gt;

This textbook is a comprehensive resource designed to bridge the gap between theoretical concepts and practical applications in the field of decision-making. This book aims to equip readers with the knowledge and tools necessary to develop and implement effective models using Excel, a widely accessible and powerful tool. From streamlining processes and optimizing marketing efforts to resource allocation and trend forecasting, this guide demonstrates how modelling can support critical organizational goals.This book demystifies the modelling process, guiding readers through each step - from understanding core principles to implementing decision-making strategies in Excel. Designed to address real-world challenges in diverse fields such as finance, logistics, healthcare, and manufacturing, this resource combines clear explanations, practical examples, and actionable insights to help readers make effective, data-driven decisions.Whether you are a beginner or an experienced user, this book provides practical guidance across multiple disciplines, including business, mathematics, education, computer science, engineering, and psychology. Academics, researchers, students, and professionals will gain the tools needed to leverage Excel modelling to enhance operational efficiency, drive sustainable success, and confidently navigate today’s complex environment.

Modelling for Decision Making: A Step-by-Step Guide Using Excel

Graduate Texts in Operations Research

The book provides a comprehensive overview of mathematical optimization models and techniques for solving facility location problems. It equips students with the theoretical foundations and practical knowledge needed to analyze real‑world location planning problems, as well as to use and adapt optimization models and methods suited for these tasks. To support this, the book offers detailed explanations of the optimization theory underlying the methods used to solve the presented location problems. In particular, it discusses Lagrangian relaxation and duality, subgradient optimization, column generation, and Benders’ decomposition in substantial depth.Each chapter concludes with a set of exercises, some of which take the form of case studies that, while fictitious, reflect realistic applications. The book is further supplemented by a Python package, pyloa. At the end of each chapter, examples show how classes and routines from this package can be applied to solve selected location problems introduced in the chapter.This book is intended for graduate students in operations research, applied mathematics, mathematics‑economics, industrial engineering, and business administration with a focus on analytics or quantitative methods. It is also a valuable resource for university instructors designing 5–15 ECTS courses on location‑planning optimization, as well as for researchers and practitioners seeking a thorough introduction to optimisation models and methods for facility location planning.

With Implementations in Python

Optimisation Models and Methods for Location Planning

From Conceptual Algorithms to Real-World Applications

Methods of Nonsmooth Optimization in Stochastic Programming

A USA Today Bestseller. A dramatic new future of work in which managers assemble exactly the expertise they need—within minutes. 2026 PROSE Award Winner: Business, Finance, and Management "If you’ve ever wished you could assemble your version of The Avengers at work, this book will help you make it happen.” —Adam Grant, #1 New York Times-bestselling author of Think Again and host of the podcast Re:Thinking Gone are the days of static organizational charts and staffing based on the manager’s rolodex and intuition. Now you can recruit any expertise you need from a global online network within minutes: an on-demand, on-the-spot expert at the exact moment that you need their help. You can right-size their involvement, too; some of those experts give a second opinion or a moment of brainstorming, whereas others join as full-fledged team members for a sustained collaborative effort. This is the future promised by flash teams, a model that The New York Times has already praised for its “revolutionary potential”: a world where experts are available anytime and everywhere, where remote work has become a norm, and where AI is in the loop to guide team decisions. In Flash Teams, award-winning management scholar Melissa Valentine and computer scientist Michael Bernstein chart the opportunities of flash teams and navigate the challenges that teams and managers will face. They distill lessons from their own work assembling and managing flash teams on demand that every manager can learn from so they can successfully use flash teams in their own organizations. Drawing on original research and industry examples, this book will help readers to: <ul><li>Recognize and source needed expertise within minutes</li><li>Anticipate and plan team designs with AI</li><li>Redesign team structures on the fly as projects evolve</li></ul> Industries are already being transformed by this new approach to teaming. Flash Teams arms leaders, managers, and entrepreneurs with the tools they need to accomplish their goals with confidence, speed, and agility.

Leading the Future of AI-Enhanced, On-Demand Work

Flash Teams

Audits are no longer random-and compliance is no longer manual. Today, artificial intelligence determines which businesses get audited, how deeply investigators dig, and whether a review escalates into penalties or quietly disappears.

AI Audit Defense &amp; Risk Reduction reveals how modern enforcement systems actually work-and how smart businesses use the same AI logic to stay protected, credible, and invisible to unnecessary scrutiny.

This book is not about fear, loopholes, or hiding income. It's about designing a business that algorithms trust.
Inside, you'll discover how AI-driven tax authorities evaluate risk, how audit scores are calculated, and how to proactively shape your financial data so your business remains statistically clean, defensible, and low-priority for investigation-year after year.
In this book, you'll learn how to:Understand how AI selects businesses for IRS audits and regulatory reviews
Identify the hidden financial patterns that silently increase audit risk
Use AI to calculate and monitor your business's audit risk score
Build a complete digital audit trail that satisfies both humans and machines
Detect compliance red flags in real time-before filings are submitted
Respond to audit inquiries strategically without escalating scrutiny
Turn past audits into intelligence that lowers future risk
Design long-term compliance systems that create "audit immunity"
Make defensible financial decisions that remain explainable years later
Transform compliance from a liability into a competitive advantage


Who this book is for:Business owners and entrepreneurs
Investors and real estate professionals
Consultants, agencies, and service firms
Online businesses and multi-entity operators
Anyone who wants to grow without triggering regulatory attention



If you want to stop worrying about audits, understand how enforcement algorithms really work, and build a business that thrives under constant observation, AI Audit Defense &amp; Risk Reduction gives you the framework, mindset, and systems to do exactly that.
In the age of AI-driven enforcement, the safest businesses aren't the smallest or quietest-they're the smartest.

How Businesses Avoid Costly IRS Investigations

AI Audit Defense & Risk Reduction

The primary objective of this work is to develop a behavioral basis for an AI algorithm to assist managers of finance, production, and marketing divisions of firms in imperfect markets. Production, sales revenue, external finance, and networth (market value of the fixed assets) have the pivotal role as objectives. However, all of them cannot be maximized simultaneously due to the interdependence among them. The managers tend to pursue the most valuable objective using the most productive strategy at each point of time. This was utilized as a basis for the AI algorithm. Non-linearities in the switches in objectives and strategies are a short run phenomenon while swaps will be preferred if firms have a long run advantage. Such observed phenomena were also incorporated in the specification of the AI algorithms. The important results are as follows. (i) In most industries the shortage of demand is not a constraint. Instead, the ability of firms to increase their strategic supply is dominant. (ii) Most firms pursue strategic supply based on the capital stock available. This indicates a preference for external finance. (iii) In the short run firms utilize working capital finance and selling costs to ensure that the sales revenue achieved is commensurate with the strategic supply. (iv) Thus, the postulate that expected demand determines the strategic supply as well as the profit maximization postulate for the short run do not appear as the priorities.

Towards an AI Algorithm for Multiple Objectives in Imperfect Markets

Perspectives in Behavioral Economics and the Economics of Behavior

Keynesian Behavioral Macroeconomics analyzes Keynes’s landmark contributions in behavioral economics and develops a new and fresh genre of macroeconomic analysis. It compels us to consider seriously the earlier-generation warnings about the impact of investors’ animal spirits and financiers’ liquidity-presence using cognitive-based and social psychology heuristics. Innovative in its subject matter, approach, theoretical development and policy prescriptions, this constructivist pluralist approach can contribute to important debates. This fresh look in macroeconomics can fruitfully be applied by macroeconomists, policymakers, and market participants to prevent effective demand shortages, stimulate the economy, preserve job creation, and impact redistribution, sustainability and social inclusion. In this timely book, Theodore Koutsobinas develops a synthesis of Keynes’s macroeconomic theory with contemporary developments in behavioral macroeconomics to analyze urgent real-world challenges, and he proposes successful solutions for macroeconomic policy. This volume uniquely explains how Keynes’s magnificent, crucial, but long-forgotten dynamics can be analyzed on the basis of behavioral foundations to explain amplified global finance cycles, booms and busts, and macroeconomic instability with harmful effects on incomes and jobs.

Keynesian Behavioral Macroeconomics

Sleep isn't passive rest, but a critical driver of performance.In high-pressure environments, sleep is often the first thing to go. Long hours are treated as commitment. Pushing through is expected. But the cost builds, often in ways we don't immediately see, leading to distraction, poor decisions, emotional reactivity and missed signals.In this groundbreaking guide, sleep neuroscientist and executive advisor Els van der Helm, PhD, shows that sleep is not just a habit to optimise. It's a system to understand.Blending cutting-edge research with real-world stories and interviews - from global executives to frontline professionals - Dr van der Helm reframes sleep as a hidden driver of performance, resilience and leadership. Her practical, science-backed six-principle framework reveals how we can: <ul><li>Identify our chronotype and align our schedule with peak performance windows</li><li>Use chronotherapy to align work, energy, and recovery across the day</li><li>Understand how REM sleep supports emotional control, creativity, and decision-making - and how to protect it</li><li>Use strategic napping to recover faster and sustain high performance</li><li>Navigate periods of poor sleep, reducing the impact of bad nights and building long-term resilience</li><li>Become a 'sleep leader,' rethinking how work and life are structured to make sustained performance possible, at work and at home</li></ul> Perfect for leaders, ambitious professionals and anyone operating in high-demand environments, Sleep Intelligence offers a new way of thinking about sleep - and how we work, recover and live as a result.

The High-Performance Blueprint for Sharper Thinking

Sleep Intelligence

Tech, War and the Fight for Humanity

Thundercloud

The Fight for the Future of Work

We Are Not Machines

International Series in Operations Research & Management Science

This innovative book explores methodologies for constructing confidence intervals for proportions. It compares existing techniques and introduces new procedures developed by the authors, emphasizing the actual coverage function to assess their effectiveness. It covers various applications, such as estimating success rates in Monte Carlo simulations, gauging electoral support, assessing project completion rates, and evaluating product reliability. It provides analysts with both point and interval estimators, highlighting how interval estimators offer precision for point estimates.

Key focus is placed on selecting appropriate confidence interval procedures and understanding their statistical properties. While traditional methods offer only approximate intervals, this work examines popular options and derives their statistical characteristics, providing guidelines for practitioners. Additionally, it discusses pointwise confidence intervals for survivor functions from randomly right-censored datasets, appealing to reliability engineers and survival analysts. It includes practical applications through functions in R, allowing practitioners to compute confidence intervals and visualize their coverage.

As the first of its kind to focus solely on this topic, the book serves as a valuable resource for advanced students and can support a one-semester course on confidence intervals for proportions, making a significant contribution to the field of statistics.

Analysis of Binary Data with Applications to Survival Analysis

Confidence Intervals for Proportions

This book provides a clear and structured guide to the international certifications and standards that organizations adopt to govern and improve their operations, products, and processes, while responding to regulatory, market, and societal demands for accountability and transparency.The book is organized into chapters dedicated to the most widely adopted standards: ISO 9001 (quality management), ISO 14001 and EMAS (environmental management), ISO 45001 (occupational health and safety), SA8000 (social responsibility), and ISO/IEC 27001 (information security). It also covers emerging governance frameworks such as B Corp certification and the United Nations Global Compact. Two concluding chapters address the practical journey of adopting a standard and the strategies for integrating multiple management systems into a coherent whole. Each chapter combines theoretical foundations with real-world case studies, helping readers understand how organizations translate these standards into practice.Offering a comparative and interdisciplinary perspective that is both rigorous and accessible, this book will be of great interest to scholars, students, managers, auditors and consultants. It helps readers not only understand each certification individually, but also see how standards interact with one another and with broader organizational strategies. Moreover, the book fills a gap between fragmented academic literature and practitioner oriented manuals by providing a balanced mix of conceptual grounding, case-informed examples, and operational tools.Matteo Podrecca
 is an Assistant Professor in the Department of Economics and Management “Marco Fanno”, University of Padova, Italy.
 Marco Sartor
 is a Full Professor in the Polytechnic Department of Engineering and Architecture, University of Udine, Italy.

Theory and Practice

Quality Management Standards

Models and Algorithms of Time-Dependent Scheduling

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