Introduction

Edmund K. Burke and Graham Kendall
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Edmund K. Burke: University of Nottingham, Automated Scheduling, Optimisation and Planning Research Group, The School of Computer Science and IT
Graham Kendall: University of Nottingham, Automated Scheduling, Optimisation and Planning Research Group, The School of Computer Science and IT

Chapter Chapter 1 in Search Methodologies, 2005, pp 5-18 from Springer

Abstract: Abstract The investigation of search and optimization technologies underpins the development of decision support systems in a wide variety of applications across industry, commerce, science and government. There is a significant level of diversity among optimization and computational search applications. This can be evidenced by noting that a very small selection of such applications includes transport scheduling, bioinformatics optimization, personnel rostering, medical decision support and timetabling. More examples of relevant applications can be seen in (2002), (2004) and (1997). The exploration of decision support methodologies is a crucially important research area. The potential impact of more effective and more efficient decision support methodologies is enormous and can be illustrated by considering just a few of the potential benefits: more efficient production scheduling can lead to significant financial savings; higher quality personnel rosters lead to a more contented workforce; more efficient healthcare scheduling will lead to faster treatment (which could save lives); more effective cutting/packing systems can reduce waste; better delivery schedules can reduce fuel emissions.

Keywords: Search Space; Local Search; Tabu Search; Travelling Salesman Problem; Soft Constraint (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1007/0-387-28356-0_1

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