Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling

Preface
Contents
Evolutionary and Memetic Computing for Project Portfolio Selection and Scheduling: An Introduction
	1 Introduction
	2 Problem Formulation
	3 Solution Methodologies
		3.1 Mathematical Optimization
		3.2 Evolutionary Computation
		3.3 Memetic Computing
	4 Summary of Chapters
	5 Guide for Readers
	References
Evolutionary Approaches for Project Portfolio Optimization: An Overview
	1 Introduction
	2 Problem Description
		2.1 Public and Social Projects
		2.2 Software/IT Projects
		2.3 R&D and Production Projects
		2.4 Construction and Infrastructure Projects
		2.5 Investment Projects
		2.6 Defense Projects
		2.7 Summary of Problem Descriptions
	3 Problem Formulation
		3.1 Basic Problem Formulation
		3.2 Public and Social Projects
		3.3 Software/IT Projects
		3.4 R&D and Production Projects
		3.5 Construction and Infrastructure Projects
		3.6 Investment Projects
		3.7 Defense Projects
		3.8 Summary of Formulations
	4 Solution Approaches
		4.1 Public and Social Projects
		4.2 Software/IT Projects
		4.3 R&D and Production Projects
		4.4 Construction and Infrastructure Projects
		4.5 Investment Projects
		4.6 Defense Projects
		4.7 Summary of Solution Approaches
	5 Summary
	References
An Introduction to Evolutionary and Memetic Algorithms for Parameter Optimization
	1 Introduction
	2 Comparison Between EAs and Classical Optimization Methods
		2.1 Robustness
		2.2 Efficiency
	3 Building Blocks of EAs
	4 Genetic Algorithm
		4.1 Initialization
		4.2 Selection
		4.3 Crossover
		4.4 Mutation
		4.5 Population Update
		4.6 Stopping Criteria
	5 Evolution Strategies
		5.1 Selection
		5.2 Recombination
		5.3 Mutation
		5.4 Adjusting the Mutation Profile
	6 Evolutionary Programming
	7 Differential Evolution
		7.1 Mutation
		7.2 Crossover
		7.3 Selection
		7.4 Recent Variants
	8 Other Relevant Methods
	9 Memetic Algorithms
	10 Summary and Conclusions
	References
An Overall Characterization of the Project Portfolio Optimization Problem and an Approach Based on Evolutionary Algorithms to Address It
	1 Introduction
	2 A Review of the Project Portfolio Selection Process
		2.1 Phases in the Project Portfolio Selection Process
		2.2 Characterizing a Plausible Project Portfolio Selection Approach
	3 Problem Statement
		3.1 Problem Description
		3.2 An Illustrative Example
		3.3 Problem Formalization
	4 An Overall Approach to Project Portfolio Selection
		4.1 Framework of the Approach
		4.2 Coping with Imperfect Information on the Criteria Impacts
		4.3 Representing Preferences
		4.4 Using Evolutionary Algorithms to Optimize Portfolios
	5 Conclusions and Future Work
	References
A New Model for the Project Portfolio Selection and Scheduling Problem with Defence Capability Options
	1 Introduction
	2 Background
		2.1 The Knapsack Problem
		2.2 Evolutionary Meta-Heuristic Approaches
		2.3 Differential Evolution
	3 Problem Formulation
		3.1 Analysis of Problem Formulation
		3.2 NP-Hardness
		3.3 Sample Problem Data
		3.4 Similarity to Existing Problems
	4 Heuristic Solution Approach
	5 Experimental Design
		5.1 Synthetic Problem Instance Generation
		5.2 Problem Instances
		5.3 Algorithmic Control Parameters
		5.4 Statistical Analysis
	6 Results
		6.1 Validating the Solution Approaches
		6.2 Effect of Seeding
		6.3 Main Results
		6.4 Summary
	7 Conclusions and Future Work
	References
Analysis of New Approaches Used in Portfolio Optimization: A Systematic Literature Review
	1 Introduction
	2 Research Method
		2.1 Research Questions
		2.2 Search Sources
		2.3 Inclusion Criteria and Exclusion Criteria
		2.4 Data Extraction
		2.5 Data Analysis
		2.6 Deviations in the Protocol
	3 Results
		3.1 Journal Impact Factor
		3.2 Classification of Methods
	4 Discussion
		4.1 Which Key Methods, Tools, or Optimization Techniques Are Used in the Portfolio Optimization Problem?
		4.2 Which Realistic Constraints Are Used?
		4.3 What Type of Analysis Is Done Regarding the Stock: Fundamental, Technical, or Mixed (Fundamental and Technical)?
		4.4 Which Software/Programming Languages Are Used?
		4.5 Recent Researches
	5 Conclusions
	6 Research Gaps
	References
A Temporal Knapsack Approach  to Defence Portfolio Selection
	1 Introduction
	2 Project and Portfolio Selection in DoD
	3 Problem Formulation
		3.1 Inherent Solution Challenges
	4 Implementation in Microsoft Excel®
	5 Performance and Budget-Value Trade-Offs
		5.1 Relaxation
		5.2 Value-Slack Trade-Offs and the Issue of Sensitivity
	6 Discussion and Future Work
	References
A Decision Support System for Planning Portfolios of Supply Chain Improvement Projects in the Semiconductor Industry
	1 Introduction
	2 Literature
	3 Decision Making Framework and Integer Programming Model
	4 Decision Support System
	5 Case Study
	6 Conclusions and Future Research
	References
Index