Scheduling practice and recent developments in flow shop and job shop scheduling

Autor:	Yenisey, Mehmet Mutlu
Přispěvatelé:	Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü., Yağmahan, Betül, B-5557-2017
Jazyk:	angličtina
Rok vydání:	2009
Předmět:	Tabu search algorithm Total tardiness M-machine Flow Shop Scheduling Permutation Flowshop No-Wait Genetic algorithm Particle swarm optimization Scatter search N-job Minimizing makespan Sequencing problem Heuristic algorithm Computer science Computer science artificial intelligence
Popis:	Each plant and/or service provider performs several tasks to satisfy customer demand. Every task consumes several resources in order to be completed. Scheduling deals with the allocation of limited resources to tasks over time. Because the resources used in manufacturing activities are very limited, scheduling becomes a very important concept in managerial decision-making. This importance draws the attention of both practitioners and academicians to scheduling. Scheduling problems usually lie in the NP-hard problem class. Difficulty especially increases as the number of jobs or machines involved increases. As the problem size increases, exact solution techniques become insufficient. This chapter provides an overview of recent developments in computational intelligence approaches to flow shop and job shop scheduling.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=od______9458::a8efdce624313f1d74625262e1f8d5ee http://hdl.handle.net/11452/24055 Zobrazit plný text záznamu