Using MAP-Elites to support policy making around Workforce Scheduling and Routing
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Neil Urquhart
,
Emma Hart
Abstract
Algorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be useful when formulating policy around the problem itself. The number of solutions that can potentially be returned by MAP-Elites is controlled by a parameter d that discretises the user-defined features into ‘bins’. For a fixed evaluation budget, increasing the number of bins increases user-choice, but at the same time, may lead to a reduction in overall quality of solutions. We undertake a study of the application of Map-Elites to a Workforce Scheduling and Routing problem, using a set of realistic instances based in London.
Zusammenfassung
Algorithmen wie MAP-Elites bieten Nutzern ein Mittel, um einen Lösungsbereich unter Rückgriff auf ein Archiv leistungsstarker Lösungen zu erkunden. Ein solches Archiv kann dem Nutzer einen Überblick über den Lösungsraum geben, der es ihm erlaubt, selbst eine Verfahrensweise für das Problem zu formulieren. Die Anzahl der möglichen Lösungen, die von MAP-Elites zurückgespielt werden, wird durch einen Parameter d gesteuert, der die benutzerdefinierten Funktionen in „Bins“ diskretisiert. Gegen ein festgelegtes Bewertungsbudget wird die Anzahl der Bins erhöht, was wiederum die Benutzerauswahl erhöht. Dies kann aber gleichzeitig zu einer Verringerung der Gesamtqualität der Lösungen führen. Wir führen eine Studie über die Anwendung von MAP-Elites für die Personaleinsatzplanung und ‑weiterleitung mit einem Set realistischer Instanzen mit Sitz in London durch.
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Articles in the same Issue
- Frontmatter
- Editorial
- EvoStar 2019: Bio-Inspired Computing and Automation
- Methoden
- Phase-space exploration of unit ensembles in energy management
- Anwendungen
- Evolutionary optimization of sliding contact positions in powered floor systems for mobile robots
- Using MAP-Elites to support policy making around Workforce Scheduling and Routing
- A computational intelligence based approach for optimized operation scheduling of energy plants
- Long term predictions of coal fired power plant data using evolved recurrent neural networks
- Process planning and scheduling optimisation with alternative recipes
- Persönliches
- Gedenkkolloquium Ernst Dieter Gilles (1935–2019)
Articles in the same Issue
- Frontmatter
- Editorial
- EvoStar 2019: Bio-Inspired Computing and Automation
- Methoden
- Phase-space exploration of unit ensembles in energy management
- Anwendungen
- Evolutionary optimization of sliding contact positions in powered floor systems for mobile robots
- Using MAP-Elites to support policy making around Workforce Scheduling and Routing
- A computational intelligence based approach for optimized operation scheduling of energy plants
- Long term predictions of coal fired power plant data using evolved recurrent neural networks
- Process planning and scheduling optimisation with alternative recipes
- Persönliches
- Gedenkkolloquium Ernst Dieter Gilles (1935–2019)
