Jingpeng Li
An Evolutionary Squeaky Wheel Optimisation Approach to Personnel Scheduling.
Mon, 10/19/2009 - 13:48 — SomNambulAuthors: Jingpeng Li, Uwe Aickelin, Edmund Burke
Subjects: Artificial Intelligence
AbstractThe quest for robust heuristics that are able to solve more than one problem
is ongoing. In this paper, we present, discuss and analyse a technique called
Evolutionary Squeaky Wheel Optimisation and apply it to two different personnel
scheduling problems. Evolutionary Squeaky Wheel Optimisation improves the
original Squeaky Wheel Optimisation's effectiveness and execution speed by
incorporating two extra steps (Selection and Mutation) for added evolution.A Component Based Heuristic Search Method with Evolutionary Eliminations.
Fri, 10/16/2009 - 04:10 — SomNambulAuthors: Jingpeng Li, Uwe Aickelin, Edmund Burke
Subjects: Artificial Intelligence
AbstractNurse rostering is a complex scheduling problem that affects hospital
personnel on a daily basis all over the world. This paper presents a new
component-based approach with evolutionary eliminations, for a nurse scheduling
problem arising at a major UK hospital. The main idea behind this technique is
to decompose a schedule into its components (i.e. the allocated shift pattern
of each nurse), and then to implement two evolutionary elimination strategies
mimicking natural selection and natural mutation process on these components
respectively to iteratively deliver better schedules.
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