Preface

Scheduling is defined as the process of assigning operations to resources over time to optimize a criterion. The requirements for scheduling mentioned in the literature include the minimization of several factors, including completion time of the set of services under consideration (the makespan), mean Work in Process (WIP), mean manufacturing time (the mean flow time), mean delay, and mean processing cost, and the maximization of productivity.

Scheduling is essential in many different fields, including e-health, high-performance computing, data science, big data, and Industry 4.0. Our book covers new aspects and uses of scheduling and load balancing, detailing challenges and new trends in the field. In three sections ergo seven chapters, we revisit the concepts of scheduling and the novelties of scheduling problems, in addition to examining new areas that are benefiting from these concepts to both improve efficiency and reduce costs.

Scheduling has a broad impact on several areas. Considering this, the content of this book is not limited to engineering, but also covers other areas such as biological, chemical, and computational fields. Thus, this book will be of interest to those working in the decision-making branches of production in various operational research areas as well as in the design of computational methods. People from diverse backgrounds like academia, industry, and research can take advantage of this volume.

#### **Prof. Dr. Rodrigo da Rosa Righi**

Professor and Researcher in the Applied Computing Graduate Program (PIPCA), Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo, Brazil

**II**

**Section 3**

and Load Balancing

*and Rodrigo da Rosa Righi*

Environment *by Tahani Aladwani*

Cloud Computing and Data Science: Exploring the Benefits

Looking at Data Science through the Lens of Scheduling

*by Diórgenes Eugênio da Silveira, Eduardo Souza dos Reis,* 

Types of Task Scheduling Algorithms in Cloud Computing

*Rodrigo Simon Bavaresco, Marcio Miguel Gomes, Cristiano André da Costa, Jorge Luis Victoria Barbosa, Rodolfo Stoffel Antunes, Alvaro Machado Júnior, Rodrigo Saad* 

of Task Scheduling on Such Environments **113**

**Chapter 6 115**

**Chapter 7 131**

**1**

Section 1

New Scheduling

Approaches

and Algorithms

Section 1

New Scheduling Approaches and Algorithms

**3**

**Chapter 1**

*Ade Jamal*

**Abstract**

Global Optimization Using Local

Course scheduling problem is a combinatorial optimization problem which is defined over a finite discrete problem whose candidate solution structure is expressed as a finite sequence of course events scheduled in available time and space resources. This problem is considered as non-deterministic polynomial complete problem which is hard to solve. Many solution methods have been studied in the past for solving the course scheduling problem, namely from the most traditional approach such as graph coloring technique; the local search family such as hill-climbing search, taboo search, and simulated annealing technique; and various population-based metaheuristic methods such as evolutionary algorithm, genetic algorithm, and swarm optimization. This article will discuss these various probabilistic optimization methods in order to gain the global optimal solution. Furthermore, inclusion of a local search in the population-based algorithm to

Search Approach for Course

Scheduling Problem

improve the global solution will be explained rigorously.

probabilistic optimization algorithm

**1. Introduction**

intelligence [1–9].

**Keywords:** course scheduling, optimization, local search, genetic algorithm,

Scheduling is the process of assigning a set of given tasks to resources by some means. Among the resources, time resource usually plays a central role in scheduling process; hence this process is often called timetabling. Besides the time resource, there are other resources involved in the scheduling process such as space or room, machine or tools, and human resources. The resources are usually subject to constraints that make scheduling problems interesting for researchers in finding an optimal solution or in developing a method for solving it. Course scheduling problem attracts researchers from the field of operation research and artificial

This manuscript will focus on the problem of university course scheduling which has several variants such as school timetabling [10] and examination scheduling [11–13]. The variation of course scheduling problem is merely due to different constraints on the resources involved in the scheduling processes. Despite of these variations, they can be considered as the same family of course scheduling problem. In the scheduling problem, courses or exams have to be assigned into time

particle swarm optimization, combinatorial optimization problem,

#### **Chapter 1**
