Lot streaming and batch scheduling: splitting and grouping jobs to improve production efficiency


Possani, Edgar (2001) Lot streaming and batch scheduling: splitting and grouping jobs to improve production efficiency. University of Southampton, Department of Mathematics, Doctoral Thesis , 162pp.

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Description/Abstract

This thesis deals with issues arising in manufacturing, in particular related
to production efficiency. Lot streaming refers to the process of splitting jobs
to move production through several stages as quickly as possible, whereas
batch scheduling refers to the process of grouping jobs to improve the use of
resources and customer satisfaction.
We use a network representation and critical path approach to analyse the
lot streaming problem of finding optimal sublot sizes and a job sequence in
a two-machine flow shop with transportation and setup times. We introduce
a model where the number of sublots for each job is not predetermined,
presenting an algorithm to assign a new sublot efficiently, and discuss a
heuristic to assign a fixed number of sublots between jobs. A model with
several identical jobs in an multiple machine flow shop is analysed through
a dominant machine approach to find optimal sublot sizes for jobs.
For batch scheduling, we tackle the NP-hard problem of scheduling jobs
on a batching machine with restricted batch size to minimise the maximum
lateness. We design a branch and bound algorithm, and develop local
search heuristics for the problem. Different neighbourhoods are compared,
one of which is an exponential sized neighbourhood that can be searched in
polynomial time. We develop dynamic programming algorithms to obtain
lower bounds and explore neighbourhoods efficiently. The performance of
the branch and bound algorithm and the local search heuristics is assessed
and supported by extensive computational tests.

Item Type: Thesis (Doctoral)
Subjects: T Technology > TS Manufactures
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Q Science > QA Mathematics
Divisions: University Structure - Pre August 2011 > School of Mathematics > Operational Research
ePrint ID: 50621
Date Deposited: 19 Mar 2008
Last Modified: 27 Mar 2014 18:33
URI: http://eprints.soton.ac.uk/id/eprint/50621

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