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Routing and scheduling for home care services : solution approaches for static and dynamic settings / von Daniela Guericke, M.Sc. Gutachter: Prof. Dr. Leena Suhl (Erstgutachter) ; Prof. Dr. Hans Kleine Büning (Zweitgutachter). Paderborn, 2016
Inhalt
Abbreviations
List of Figures
List of Tables
Introduction
Scope of the thesis
Structure
Planning home care services
Definition and description of home care services
Development of the home care sector
Planning problems of home care providers
Strategic planning problems
Tactical planning problems
Operational planning problems
Routing and scheduling home care services
Definitions
Planning tasks and requirements
Objectives
Dependency between routing and nurse scheduling
Problem settings
Basic models and solution approaches
Operations research methods
Mixed-integer programming
Metaheuristics
Related planning problems
Variants of the vehicle routing problem
The nurse rostering problem
Technician routing and scheduling
State-of-the-art in home care routing and scheduling
Daily routing and scheduling in static setting
Decomposed assignment and routing
Integrated routing and scheduling
Multi-day routing and scheduling in static setting
Decomposed routing and scheduling
Integrated routing and scheduling
Consideration of additional working regulations
Routing and scheduling in a dynamic setting
Research opportunities
Research goals
Exact solution approach for the static setting
Problem setting and notation
Working regulations
Network structure
Formalization of the problem setting
Decision Variables
Mixed integer program
Consideration of Generic Working Regulations
Test instances
Numerical results
Results for small instances
Results for test set instances
Analysis of increased computation time
Summary
Heuristic solution approaches for the static setting
Shared subproblems and methods
Notation and solution representation
Determination of candidate tours and positions for job insertion
Insertion of jobs into routes
Removal of jobs from tours
Construction heuristic
Large neighborhood search
Acceptance of solutions
Large neighborhood operator
Adaptive large neighborhood search
Destroy operators
Repair operators
Reduced variable neighborhood search
Neighborhood operators
Parameter tuning
Numerical results
Comparison of exact and heuristic solution approaches
Comparison of heuristics
Impact of working regulations
Summary
Heuristic solution approaches for the dynamic setting
Planning in a dynamic setting
Definitions
Extension of instance and solution representation
Modeling continuity in a dynamic setting
Continuity metrics
Overall continuity measurement and trade off
Modes for continuity calculation
Heuristic rolling horizon approach
Analysis of results
Test instances for a dynamic setting
Comparison of continuity metrics
Comparison of continuity modes
Evaluation of rolling horizon approach
Summary
Concluding remarks
Summary and critical review
Opportunities for future research
Bibliography
Instance information
Detailed results for the exact approach in a static setting
Detailed results for the heuristic approaches in a static setting
Parameter settings before and after algorithm configuration
Averaged results per instance
Additional figures
Normalization factors and additional formulas for continuity metrics
Normalization factors
Definitions of continuity modes for remaining metrics
Further results for the solution approach in a dynamic setting
Comparison of continuity metrics with weight 1.0
Influence of time-dependent weighting in two week planning period
Analysis of planning period length for scenarios increase and extreme
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