Recent Advances in Computational Optimization: Results of the Workshop on Computational Optimization WCO 2021 (Studies in Computational Intelligence, 1044)

✍ Scribed by Stefka Fidanova (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 388
• Edition: 1st ed. 2022
• Category: Library

✦ Synopsis

This book presents recent advances in computational optimization. The book includes important real problems like modeling of physical processes, parameter settings for controlling different processes, transportation problems, machine scheduling, air pollution modeling, solving multiple integrals and systems of differential and integral equations which describe real processes, solving engineering and financial problems.
It shows how to develop algorithms for them based on new intelligent methods like evolutionary computations, ant colony optimization, constrain programming Monte Carlo method and others. This research demonstrates how some real-world problems arising in engineering, economics and other domains can be formulated as optimization problems.

✦ Table of Contents

Organization
Preface
Contents
Learning to Optimize
1 Introduction
2 Related Work
3 Learning Emergence with Cartesian Genetic Programming
4 Results
5 Conclusion
References
Optimal Seating Assignment in the COVID-19 Era via Quantum Computing
1 Introduction
2 Quantum Computing Approach
3 Quantum Computing Solvers
3.1 Quadratic Unconstrained Binary Optimization (QUBO)
3.2 QBSolv
3.3 D-Wave Quantum-Classical Hybrid solver
4 A Case-Study: The Seating Arrangement Optimization Problem
4.1 Problem Description
4.2 Mathematical Programming Formulation
4.3 QUBO Formulation
4.4 Parametric Coefficients Calibration
5 Computational Results
5.1 QUBO model size
5.2 Quality of the solutions
5.3 Efficiency of the solvers
6 Conclusions
References
Hybrid Ant Colony Optimization Algorithms—Behaviour Investigation Based on Intuitionistic Fuzzy Logic
1 Introduction
2 Multiple Knapsack Problem
3 Ant Colony Optimization Algorithm
4 Local Search Procedure
5 InterCriteria Analysis
6 Computational Results and Discussion
6.1 Results of Application of mu minusµ-Biased ICrA
6.2 Results of Application of nu minusν-Biased ICrA
6.3 Results of Application of Unbiased ICrA
6.4 Results of Application of Balanced ICrA
7 Conclusion
References
Scheduling Algorithms for Single Machine Problem with Release and Delivery Times
1 Introduction
2 IJR and ICA Scheduling Algorithms
2.1 Algorithm IJR
3 Combined Scheduling Algorithm ICA
4 Properties of the Schedule Constructed by the Algorithm ICA
5 Combined Scheduling for the Forward and the Inverse Problem FIICA
5.1 Algorithm FIICA
6 Computational Experiment
7 Conclusion
References
Key Performance Indicators to Improve e-Mail Service Quality Through ITIL Framework
1 Introduction
2 Problem Discussion
3 Service Dependencies and Available Approaches
4 Key Performance Indicators Design
4.1 Timeline of ITIL Implementation
4.2 KPIs Classification and Formulation
5 Group Decision Making for KPIs Selection
6 Conclusion
References
Contemporary Bioprocesses Control Algorithms for Educational Purposes
1 Introduction
2 Mathematical Model and Process Monitoring
2.1 Mathematical Model for Control Purposes
2.2 Observer Design
3 Adaptive Linearizing Control Design
3.1 Transformation of the Model for Control
3.2 Observer-Based Estimator of Unknown Kinetic Parameters
3.3 Adaptive Linearizing Control Design
4 Building-In the Control Algorithms in InSEMCoBio
5 Results and Discussion
6 Conclusion
References
Monitoring a Fleet of Autonomous Vehicles Through A Like Algorithms and Reinforcement Learning
1 Introduction
2 The SPR: Shortest Path under Risk Model
2.1 Transit Network and Risk Function
2.2 Routing Strategies and the SPR Problem
2.3 Some Structural Results
2.4 A Consequence: Risk Versus Distance Reformulation of the SPR Model
2.5 Discussion About the Complexity
3 Algorithms
3.1 Decision Scheme
3.2 A Local Search Algorithm Involving Dynamic Programming
3.3 A A Algorithm
3.4 Discussion: The Decision Set upper Lamda
4 Speeding Algorithms through Statistical Learning Techniques
4.1 Bounding Decisions
4.2 Bounding States
5 Numerical Experiments
6 Conclusion
References
Rather Good In, Good Out'' ThanGarbage In, Garbage Out'': A Comparison of Various Discrete Subsampling Algorithms Using COVID-19 Data Without a Response Variable
1 Introduction
2 Proposed Research Methodology
2.1 Formal Description of a Dataset Used for Subsampling
2.2 Metrics for Controlling the Quality of the Subsampling
2.3 Subsampling Algorithms
3 Results
4 Conclusion
References
Using Temporal Dummy Players in Cost-Sharing Games
1 Introduction
1.1 Background
1.2 Notation and Problem Statement
1.3 Related Work
1.4 Our Results
2 Hardness Proof for General Networks
3 Cost-Sharing Games on Parallel Links
3.1 Preliminaries and Observations
3.2 The Naive Solution
4 Convergence to the Social Optimum
4.1 Max Cost-reduction Heuristic
4.2 Balancing Heuristic
4.3 Exhaustive Heuristic
4.4 Performance Measure Comparison
5 Exploit a Given Number of Dummy Players
5.1 Max Cost-reduction Heuristic
5.2 Balancing Heuristic
5.3 Exhaustive Heuristic
6 Experimental Results
7 Conclusions and Open Problems
References
Index-Matrix Interpretation of a Two-Stage Three-Dimensional Intuitionistic Fuzzy Transportation Problem
1 Introduction
2 Basic Definitions of the Concepts of Index Matrices and Intuitionist Fuzzy Logic
2.1 Short Remarks on Intuitionistic Fuzzy (IF) logic
2.2 Definition, Operations and Relations Over 3-D Intuitionistic Fuzzy IMs
3 Index-Matrix Interpretation of a Two-Stage Three-dimensional Intuitionistic Fuzzy TP
3.1 Algorithm for Finding of an Optimal Solution of the 2-S 3-D IFTP
3.2 An Application of the Optimal Algorithm of 2-S 3-D IFTP
4 Conclusion
References
Application of an Interval-Valued Intuitionistic Fuzzy Decision-Making Method in Outsourcing Using a Software Program
1 Introduction
2 Basic Concepts of IMs and IVIF Logic
2.1 Interval-Valued Intuitionistic Fuzzy Logic
2.2 Interval-Valued Intuitionistic Fuzzy Index Matrices
3 An Optimal Interval-Valued Intuitionistic Fuzzy Selection for the Outsourcing Service Providers
3.1 Optimal IVIF Selection of the Providers
3.2 A Software Program for Optimal IVIF Selection of the Providers
3.3 A Case Study
4 Conclusion
References
Combinatorial Etudes and Number Theory
1 Morse Sequence
2 Formulation of the Main Results
3 Proof of the Main Results
3.1 Proof of Corollary 1
3.2 Proof of Proposition 1
3.3 Proof of Proposition2
3.4 Proof of Proposition 3
3.5 Proof of Proposition4
4 Arithmetic Progression Theorem
4.1 Product of Arithmetic Progressions
4.2 Generalization of Arithmetic Progression Theorem
References
Multicriteria Optimization of an Algorithm for Charging Energy Storage Elements
1 Introduction
2 A Short Description of the Studied Energy Storage System
3 The Basic Algorithm
4 The Optimized Algorithm
5 Simulation Results and Comparison of the Studied Algorithms
6 Conclusion
References
Optimized Nano Grid Approach for Small Critical Loads
1 Introduction
2 The Need of Photovoltaics
3 The Need of Microgrids
4 Determine the Loads
5 Numerical Example
6 Conclusion
References
Optimized Monte Carlo Methods for Sensitivity Analysis for Large-Scale Air Pollution Model
1 Introduction
2 The Description of the Danish Eulerian Model
3 Latin Hypercube Sampling
4 The van der Corput Sequence
5 Sensitivity Studies with Respect to Emission Levels
6 Sensitivity Studies with Respect to Chemical Reactions Rates
7 Conclusion
References
On a Full Monte Carlo Approach to Computational Finance
1 Introduction
2 Problem Settings and Motivation
3 Quasi-Monte Carlo Methods for Numerical Integration Based on Lattice Sequences
3.1 Lattice Sequence Based on Fibonacci Generating Vector
3.2 Polynomial Lattice Rule
3.3 Lattice Sequences Based on Optimal Vectors
4 Numerical Examples and Results
5 Conclusion
References
Advanced Monte Carlo Methods to Neural Networks
1 Introduction
2 Formulation of the Problem
3 The Description of the Stochastic Approaches
4 Numerical Results
5 Conclusion
References
An Efficient Adaptive Monte Carlo Approach for Multidimensional Quantum Mechanics
1 Introduction
2 The Wigner Monte Carlo Method
3 Numerical Examples
4 Conclusions
References
An Overview of Lattice and Adaptive Approaches for Multidimensional Integrals
1 Introduction
2 Adaptive Approach
3 Lattice Rules
4 Numerical Examples
5 Conclusion
References
Advanced Biased Stochastic Approach for Solving Fredholm Integral Equations
1 Introduction
2 Formulation of the Problem
3 Biased Stochastic Approach
3.1 Monte Carlo Method for Integral Equations
3.2 Error Analysed of the Biased Stochastic Approach
3.3 Error Balancing Conditions for the Biased Stochastic Approach
4 Unbiased Stochastic Approach
4.1 Unbiased Approach for a Simplified Problem
4.2 Unbiased Approach for the General Problem
5 Numerical Examples and Discussion
5.1 Simple Case
5.2 Application to Biology
5.3 Application to Neural Networks
5.4 Application to Physics
5.5 A Comparison Between the Biased and the Unbiased Algorithm
6 Conclusion
References
Improving Performance of Low-Cost Sensors Using Machine Learning Calibration with a 2-Step Model
1 Introduction
2 Background of Air Quality Monitoring
2.1 Air Quality Monitoring Systems
2.2 Opportunities and Disadvantages of Wireless Low-Cost Stations
2.3 Effects from Humidity and Height
2.4 Reference Instrument
2.5 PM Sensors
2.6 The Wireless Network
3 Data Calibration Model
3.1 Datasets and Model
3.2 Methods
4 Application of the Model on Wireless Sensor Network
4.1 Dataset and Model
4.2 Modelling the Pressure Measurement
5 Results and Evaluation
5.1 Evaluation of the Results for Relative Humidity
5.2 Results of the Calibration Model
5.3 Improvements of the Model Through Unsupervised Learning
5.4 Results from the Application on the WSN
6 Conclusion and Future Research
References
Author Index