Diseño de un DSS para resolver el problema de Ruteo
-
Upload
james-edward-tomala-robles -
Category
Business
-
view
723 -
download
0
description
Transcript of Diseño de un DSS para resolver el problema de Ruteo
![Page 1: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/1.jpg)
Route Planning Software and Hybrid Genetic Algorithm Design of a DSS to solve the routing problem in a Courier Service
Ph. D. Walter Vaca Arellano (EPN)
Ing. James Tomalá Robles
(UTE Universidad Tecnológica Equinoccial)
Ing. Johnny Pincay Villa (ESPOL)
EcuadorALIO-INFORMS meeting Buenos Aires
2010
Instituto de Ciencias Matemáticas-ESPOL
![Page 2: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/2.jpg)
Motivation
In Ecuador, there are approximately 800 courier agencies, and all of them use empirical methods to
plan their routes
It directly affects the two objectives of integrated
logistics
Problem: the absence of a decision support system applying heuristic procedures for the transport operations planning of a courier company
![Page 3: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/3.jpg)
Objectives1. Obtain a model
for courier delivery problem.
2. Design and develop a Metaheuristic based on genetic algorithm.
3. Propose a DSS design that uses the developed metaheuristic.
![Page 4: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/4.jpg)
Mathematic formulationCapacitated Vehicle Routing Problem with smooth Time windows
Visitar todos los clientes una sola vez.
Todos los vehículos salen del depósito.
![Page 5: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/5.jpg)
Mathematic formulation
Cada ruta es realizada por un solo vehículo.
La demanda no puede superar la capacidad del vehículo.
Se respeta la atención más temprana del cliente y se permite atraso.
Continuidad del tiempo y eliminación de subtours. Miller, Tucker y Zemlin [2].
Var. Binaria y positivos
![Page 6: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/6.jpg)
GA for CVRPTW
Evolutionary Strategy
local search heuristics
Restrictions of time windows
GA for CVRPTW
Thangiagh [16], Bonrostro, Zhu[17], Homberger y Gehring [23]
On a review of GA publications, we may be concluded that GA requires modification of the classic genetic operators such as:
a) Redesign of the mutation and crossover operators.b) Inclusion of local search to improve solutions.c)And considerations of time constrains
![Page 7: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/7.jpg)
Generation of population
Reproductive And
improving stage
BEGIN /* Hybrid Genetic Algorithm*/
Cargar_datos() //reads data from a filet←0
Po←generacion_poblacion_incial()
WHILE (t ≤ NUM_ITERACIONES) DO
/* Produce new generation*/
evaluacion_poblacion(Pt)
Pt<-mutacion_padres(Pt)
Pt← generar_hijos(Pt) // Produce new individuals with strategy (µ, λ )-EA t←t+1
END
END
Half - insertion heuristicHalf- Ramdomly
improving routesunifies routes
Replace if the child is better than one parent
The metaheuristic
![Page 8: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/8.jpg)
chromosome representation
• chromosome:
1
0Dep
7
3
5
8
4
6
2
2
34
3
11
1
2
2
1
2
2 8 3 9 7 4 6 10 5 1
It adopts the permutation representation of integers, where the routes separator is a number greater than n, where n is the number of clients
![Page 9: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/9.jpg)
evaluation , Fitness, Selection
• cost of the route:
• Penalty for delay :
• Cost of the solution (Fitness):
• Selection:
ordering the individuals in the population according to their fitness, that is, lowest to highest cost, and randomly selects among which are located below from 40th percentile.
![Page 10: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/10.jpg)
Mutation
improve routes
unify routes
For i=1 ; i<= MOV_MUT
Select a local search operator{2-Opt *, relocation , exchange }Operator is applied
It tries to delete a route
Based on Homberger y Gehring [16].
![Page 11: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/11.jpg)
combination operator
fatherBest routes
motherBest routes
Child
Inherit
The best
Based on uniform Crossover (UC) Áslaug Sóley Bjarnadóttir [11]
The combination strategy selects the best routes from the parents and insert them to the child provided it’s not conflict.
![Page 12: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/12.jpg)
Proposal DSS
BD: Orders,demand
the TMS (Transportation managemen system)
WEB APPLICATION:DSS
planningmodule
APIGoogle Maps
component that calculates the distances between each pair of
customersInternet Hybrid GA
(Metaheurística )
Road and georeferential
DATA
![Page 13: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/13.jpg)
Test results of solomon
optimum our solution
InstanceNumber of routes
Cost Number of routes
Cost
C101 10 827.30 10 828.94C102 10 827.30 10 828.94R104 10 982.010 10 1174.84R111 12 1048.70 11 1316.00RC103 11 1258.0 11 1424.34
The developed strategy to solve the problem requires less computational effort when data is grouped by area, it was found that in these cases, the number of iterations needed to reach a good solution is less than 40. On the other hand, we must increase the number of iterations when customers are completely randomly distributed in a geographical region.
![Page 14: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/14.jpg)
Results – Study Case
RUT
A ORDEN DE VISITAS
CLIENTE
S
1
0-5-33-66-39-20-45-26-32-48-61-34-17-9-21-27-10-56-4-
12-29-0 20
2
0-7-38-37-23-57-24-35-52-25-54-65-51-60-43-62-36-63-
55-15-49-0 20
3 0-14-44-18-47-22-13-16-53-40-31-30-59-3-46-6-58-0 16
4 0-1-50-19-28-11-8-42-41-2-64-0 10RUTAS T ESPERA T ATRASO T SERVICIO T RUTA TOTAL
1 0:22:12 0:00:00 2:31:48 2:10:12 5:04:12
2 0:10:48 0:00:36 2:11:24 1:57:36 4:20:24
3 0:00:00 0:00:00 1:54:00 1:12:00 3:06:00
4 0:00:00 0:00:00 1:58:12 1:16:48 3:15:00
TOTAL 0:33:00 0:00:36 8:35:24 6:36:36 15:45:36
The developed Metaheuristic increases the level of service to 98.46%
According to company data, the average
service level of the first quarter of 2009, was 69.35%, ie, 20 clients were not treated on
time.
![Page 15: Diseño de un DSS para resolver el problema de Ruteo](https://reader036.fdocuments.us/reader036/viewer/2022062313/559044cb1a28ab2a4a8b4771/html5/thumbnails/15.jpg)
Example prototype using the Google Maps API
• available: www.ecualogistic.com/ruteo.php
The example prototype shows the solution of the case study.Each client has been located on the map according to their geographical location , additionally displays data such as order of visit, time of arrival and departure time. it was developed using javascript and dynamic language php.