This book presents social welfare functions as a unified multidisciplinary framework for various resource allocation problems. By measuring the impact of local decisions on broader society, social welfare functions enable “socialized” decisions and thereby produce an emergent property that “global” balance and welfare emerge from “local” welfare-maximizing behaviors. Social welfare functions are originally used in economics to quantify income welfare, jointly considering average and inequality to arrive at better measures of welfare than average alone. Wishing the readers to find opportunities for their problems of interest, this book introduces research results of social welfare functions applied in five different engineering applications, defining welfare metrics pertaining to the characteristics of the application. The “energy welfare” in wireless sensor network measures richness of distributed sensors in energy. The “preparedness welfare” in emergency medical services quantifies the preparedness level of an entire service area by aggregating preparedness levels of individual zones. The “preference welfare” in intelligent shared environments represents the opinions of real people for groups. The “resource welfare” in multi-robot task allocation quantifies the efficiency of utilizing distributed resources across robots. The “utility welfare” in complex cyber-physical systems quantifies the impact of local resource sharing decisions on the broader task communities.
Author(s): Francisco Munoz, Ashutosh Nayak, Seokcheon Lee
Series: Automation, Collaboration, & E-Services, 13
Publisher: Springer
Year: 2022
Language: English
Pages: 100
City: Cham
Preface
About This Book
Contents
1 Introduction to Engineering Applications of Social Welfare Functions
1.1 Introduction
1.1.1 Social Welfare Functions
1.1.2 Implications of Social Welfare Functions in Engineering Applications
References
2 Routing in Wireless Sensor Networks—Energy Welfare
2.1 Introduction to Wireless Sensor Networks
2.1.1 Centralized and Distributed Approaches for Data Routing
2.1.2 Energy-Efficiency, Energy-Balance, and Network Lifetime
2.2 The MaxEW Algorithm
2.2.1 MaxEW Routing Decisions
2.2.2 MaxEW Algorithm in Detail
2.3 Performance Evaluation of the MaxEW Algorithm
2.3.1 Lifetime Analysis
2.3.2 Robustness to Event Generation Patterns
2.3.3 Effect of the Neighbor Communication Range in MaxEW Algorithm
2.4 Summary
References
3 Ambulance Dispatching—Preparedness Welfare
3.1 Introduction to Emergency Medical Services (EMS) and Ambulance Dispatching
3.2 Preparedness-Based Ambulance Dispatching Algorithm
3.3 Improving Robustness of Composite Algorithm with Social Welfare Functions
3.4 Performance of Composite Algorithm with Social Welfare Functions
3.5 Summary
References
4 Group Decision Making in Intelligent Shared Environments—Preference Welfare
4.1 Introduction to Intelligent Shared Environments
4.2 Social Welfare as an Aggregate Function
4.2.1 Metrics of Distance Measure on Orders
4.2.2 Alternative Social Welfare Functions
4.2.3 The Masthoff’s Experiment
4.2.4 Incorporation of Social Influence
4.3 Performance of Social Welfare as Aggregate Functions
4.4 Summary
References
5 Task Allocation in Multi-robot Systems—Resource Welfare
5.1 Introduction to Multi-robot Systems
5.2 Task Allocation Using a Social Welfare Function
5.2.1 Resource Welfare
5.2.2 Welfare-Based Algorithm
5.3 Performance of the Welfare-Based Algorithm
5.3.1 Simulated Experiment #1
5.3.2 Simulated Experiment #2
5.4 Summary
References
6 Resource Sharing in Cyber-Physical Systems—Utility Welfare
6.1 Introduction to Resource Sharing-Based Framework (RSBF)
6.1.1 Fundamentals of RSBF
6.1.2 Utility Functions in RSBF
6.1.3 Coordination Among Local Coordinators
6.2 Application of RSBF to Flexible Job Shop Scheduling in Smart Factories
6.2.1 RSBF Framework to Solve the FJSP in Smart Factories
6.2.2 Steps to Implement RSBF to Solve the FJSP
6.2.3 Performance of RSBF Application to the FJSP
6.3 Application of RSBF to Other Cyber-Physical Systems
6.3.1 Optimal Energy Distribution Through a Smart Grid
6.3.2 Optimal Information Routing in Resource-Constraint Multi-Robot Systems
6.4 Summary
References
7 Conclusion, Limitations, and Research Opportunities
7.1 Conclusion and Discussion
7.2 Limitation and Challenges
7.3 Research Opportunities in Emerging Applications
7.3.1 Production Scheduling
7.3.2 Foodbank Operation Guidance
7.3.3 Multi-Robot Navigation
References
Index
