master thesis midway defending

7/25/2019 Master Thesis Midway Defending

1/19

Master Thesis Midway

DefendingJob-shop Scheduling Approach

to Order-picking Problem

!"#!"$ %nternational &ni'ersity "

Ad'isor( Assoc)Prof) *o ThanhPhongStudent( Tran +uoc Dat


2/19

,ontents

%-,ompleted ,ontents

") elationship between OrderPicking and Jobshop

) Ob.ecti'e

/) Modelling

0)elationship between modules %%-Ongoing ,ontents

!"#!"$ %nternational &ni'ersity


3/19

Acti'ities in logistic center

!"#!"$ %nternational &ni'ersity /


4/19

")" elationship between OrderPicking and Jobshop Problem

Order-Picking JobShop Problem

Order Job

Shelf or %tem Machine

Se1uence of picking products Process se1uence

Picking time Machine time

!"#!"$ %nternational &ni'ersity 0


5/19

") Ob.ecti'e

2uild a decision support tool for Order PickersScheduling in the warehouse(

Minimize Travel Distance for each

picker

Balance the work load among pickers-Min Deviation

Minimize Makespan of all pickers



6/19

")/ Mathematical formulation

Minimize Distance between ! items"

Parameter"

s( source node

t( target node

di.( distance between item i and item .

#ariables"

4i.( binary 'ariable5 e1ual " if arc 6i5.7 is inthe shortest path and e1ual # otherwise)

!"#!"$ %nternational &ni'ersity $


7/19

")/ Mathematicalformulation

Minimize Distance between !items"


s. t :

1, if ;

1, if ;

0, otherwise.

ij ij

ij A

ij ji

j j

minimize x

i

d

s

x x i t

=

= =


8/19


Minimize Distance for each Batch

Parameter"

ci.( minimum distance from item i toitem .

9:;#5


9/19


Minimize Distance for each Batch

!"#!"$ %nternational &ni'ersity ?

0 # , j 0

0, #

0,i#j

min . (1)

s. :

1 (2)

1 (3)

0 1, interger

n n

ij ij

i j i

n

ij

i i j

n

ij

j

ij ij

c x

t

x

x

x x

= =

=

=

=

=


10/19


Minimize Deviation between batches Parameters

J( the set of customer orders5

%( the set of feasible batches5

,( the capacity of the picking de'ice5 c.(the capacity re1uired for order . 6. @ J75

di( the length of the picking tour in which all orders of a batch iare collected)

#ariable

ai.( binary 'ariable5 an order . is included in a batch i 6ai.: "7or not 6ai.: #75

4i( binary 'ariable5 if a batch i is chosen 64i: "7 or not 64i: #7)

!"#!"$ %nternational &ni'ersity "#


11/19


Minimize Deviation betweenbatches

!"#!"$ %nternational &ni'ersity ""


12/19


Minimize Makespan for all batches

Parameters"

9( the set of all operations 6i5 .7

A( the set of all routing constraints 6i5 .7 6h5 .7

pi.( processing time of .ob . on machine .

#ariables"

,ma4( Makespan

yi.(the starting time of operation 6i5 .7

!"#!"$ %nternational &ni'ersity "


13/19


Minimize Makespan for allbatches

!"#!"$ %nternational &ni'ersity "/

max

max

Min ;

s . t :

-Makespan is the argest !ompetion time:

( , )

-"onj#n!ti$e ar!s:

( , ) ( , )

-%isj#n!ti$e ar!s :

ij ij

hj ij ij

ij ik ik

ik ij ij

C

C y p for all i j

y y p for all i j h j A

y y p or

y y p for

= +

= +

+

+

( )

-&on-negati

( , )

$e:

0

( , ) 1..

,

.

yij fo

al

r al

l i j and i k i

l

m

i j N

=


14/19

")0 elationship betweenmodules

% code by ,B language) %nclude /main Module(

-2atching Module

-TSP Module

-Jobshop Module

!"#!"$ %nternational &ni'ersity "0


15/19

!"#!"$ %nternational &ni'ersity "3


16/19

")0 elationship betweenmodules

Batching Mod$le TSP Mod$le JobshopMod$le

Data%np$t

-9umber of Order-Total %tems-Cist item for each

Order-9umber of2atch6Picker7-Minimum Distance ineach 2atch

-DistanceMatri4

between%tems 6Cayout7-Cist %tems ineach 2atch

-Se1uences%tems in each

2atch-Distance Matri4between %tems6Cayout7

DataO$tp$t

-Cist Orders in each2atch6 -%nput to Job-shop Module7-Cist %tems in each2atch 6%nput to TSPModule7

-Se1uences%tems in each

2atch

-Order PickingPlan

!"#!"$ %nternational &ni'ersity "$


17/19

%%-Ongoing ,ontents

")Cink between TSP and 2atchingModule

)Cink between 2atching ' JobshopModule

/) Testing with diEerent layouts6D-/D7

0) ,ompare other schedulingmethods)

3) Simulate Model in AF9A software!"#!"$ %nternational &ni'ersity "8


18/19

eferrences

[1]Job-shop Scheduling Approach to Order-picking Problem,Yukiyasu Iwasaki, Ikuo Suzuki, Masahito Yamamoto and MasashiFurukawa, Vol. 26, No. , !!. 1"#1"$, 2"1.

[2] Batching orders in warehouses by minimizing travel distancewith genetic algorithms, %hih&Min' (su, )ai&Yin' %h*n, Mu&%h*n %h*n,

+!!liations o- *n*ti +l'orithms in Industry, Volum* /6, Issu* 2,

F*0ruary 2""/, a'*s 16$#13 [] Solving Travelling Salemans Problem sing !enetic Algorithm

Based On "euristic #rossover And $utation Operator, Int*rnational4ournal o- 5*s*arh in n'in**rin' 7 8*hnolo'y, Vol. 2, Issu* 2, F*02"19, 2&9

[9] $ulti-Ob%ective routing and scheduling o& order pickers in awarehouse, :al;zs Moln;r and yor'y


19/19

T&'() *O+ ,O *O+

'TT.(T%O(

!"#!"$ %nternational &ni'ersity "?

master thesis midway defending

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