Meet the editors

Dr. Donald Davendra is Professor and Chair of Computer Science at Central Washington University, USA. He has a PhD in Technical Cybernetics from Tomas Bata University in Zlín, Czech Republic. His research background is in optimization algorithms, intelligent manufacturing systems, high-performance computing, and chaos systems. He has edited three books and numerous journal papers, book chapters, and conference publi-

cations in the field of computational intelligence.

Dr. Magdalena Bialic-Davendra has a PhD in Finance from Tomas Bata University in Zlín, Czech Republic. She is author and co-author of more than thirty-five scientific articles. Her research interests include wildfire modeling, business clusters, operations research, and management science.

Contents

Salesman Problem

*by Weiqi Li*

*Magdalena Bialic-Davendra*

**Preface III**

**Chapter 1 1**

**Chapter 2 7**

**Chapter 3 29**

**Chapter 4 45**

**Chapter 5 63**

Introductory Chapter: Traveling Salesman Problem - An Overview

Solution Attractor of Local Search System: A Method to Reduce Computational Complexity of the Traveling Salesman Problem

Accelerating DNA Computing via PLP-qPCR Answer Read out

Comparative Study of Algorithms Metaheuristics Based Applied to the Solution of the Capacitated Vehicle Routing Problem

*by Fusheng Xiong, Michael Kuby and Wayne D. Frasch*

*by Donald Davendra and Magdalena Bialic-Davendra*

*by Donald Davendra, Magdalena Metlicka and*

to Solve Traveling Salesman Problems

*by Fernando Francisco Sandoya Sánchez, Carmen Andrea Letamendi Lazo and Fanny Yamel Sanabria Quiñónez*

CUDA Accelerated 2-OPT Local Search for the Traveling

## Contents


Preface

The Traveling Salesman Problem (TSP) is widely considered one of the most intensively studied problems in computational mathematics and operations research. Since its inception in the 1800s, it has become the poster child for computational complexity research and Graph Theory. A number of problems have been transformed to a TSP problem, and its application base extends into scheduling, manufacturing, routing, and logistics, among others. With the advent of highperformance computing and advanced meta-heuristics such as Graphical Processing Unit (GPU) programming and Swarm-based algorithms, the TSP problem is positioned firmly as the go-to problem in the development of the next generation

This book is targeted to students and researchers. It encompasses the latest trends in TSP applications, including both theory and practical aspects, with emphasis on cutting-edge algorithms that incorporate unique paradigms such as high-

performance computing using GPUs, software accelerators, and meta-heuristics.

**Donald Davendra**

Ellensburg, USA

Ellensburg, USA

Department of Computer Science, Central Washington University,

Department of Economics and Department of Finance & Supply Chain Management, Central Washington University,

**Magdalena Bialic-Davendra**

**Dedicated to Kinga**

of intelligent heuristics.
