An Evolutionary Squeaky Wheel Optimisation Approach to Personnel Scheduling

10/16/2009
by   Uwe Aickelin, et al.
0

The 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. In the Evolutionary Squeaky Wheel Optimisation, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping conditions are reached. The aim of the Analysis step is to identify below average solution components by calculating a fitness value for all components. The Selection step then chooses amongst these underperformers and discards some probabilistically based on fitness. The Mutation step further discards a few components at random. Solutions can become incomplete and thus repairs may be required. The repairs are carried out by using the Prioritization to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, improvement in the Evolutionary Squeaky Wheel Optimisation is achieved by selective solution disruption mixed with interative improvement and constructive repair. Strong experimental results are reported on two different domains of personnel scheduling: bus and rail driver scheduling and hospital nurse scheduling.

READ FULL TEXT
research
04/09/2020

Analysis of the Performance of Algorithm Configurators for Search Heuristics with Global Mutation Operators

Recently it has been proved that a simple algorithm configurator called ...
research
10/14/2009

A Component Based Heuristic Search Method with Evolutionary Eliminations

Nurse rostering is a complex scheduling problem that affects hospital pe...
research
05/06/2019

Evolutionary Optimisation of Real-Time Systems and Networks

The design space of networked embedded systems is very large, posing cha...
research
02/10/2021

Advanced Ore Mine Optimisation under Uncertainty Using Evolution

In this paper, we investigate the impact of uncertainty in advanced ore ...
research
06/01/2018

Fast Artificial Immune Systems

Various studies have shown that characteristic Artificial Immune System ...
research
05/08/2021

A Crossover That Matches Diverse Parents Together in Evolutionary Algorithms

Crossover and mutation are the two main operators that lead to new solut...
research
11/29/2019

Value-driven Manufacturing Planning using Cloud-based Evolutionary Optimisation

This paper considers manufacturing planning and scheduling of manufactur...

Please sign up or login with your details

Forgot password? Click here to reset