├── .gitignore ├── README.md ├── pickup and delivery.xlsx └── vrppnd.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | MANIFEST 27 | 28 | # PyInstaller 29 | # Usually these files are written by a python script from a template 30 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 31 | *.manifest 32 | *.spec 33 | 34 | # Installer logs 35 | pip-log.txt 36 | pip-delete-this-directory.txt 37 | 38 | # Unit test / coverage reports 39 | htmlcov/ 40 | .tox/ 41 | .coverage 42 | .coverage.* 43 | .cache 44 | nosetests.xml 45 | coverage.xml 46 | *.cover 47 | .hypothesis/ 48 | .pytest_cache/ 49 | 50 | # Translations 51 | *.mo 52 | *.pot 53 | 54 | # Django stuff: 55 | *.log 56 | local_settings.py 57 | db.sqlite3 58 | 59 | # Flask stuff: 60 | instance/ 61 | .webassets-cache 62 | 63 | # Scrapy stuff: 64 | .scrapy 65 | 66 | # Sphinx documentation 67 | docs/_build/ 68 | 69 | # PyBuilder 70 | target/ 71 | 72 | # Jupyter Notebook 73 | .ipynb_checkpoints 74 | 75 | # pyenv 76 | .python-version 77 | 78 | # celery beat schedule file 79 | celerybeat-schedule 80 | 81 | # SageMath parsed files 82 | *.sage.py 83 | 84 | # Environments 85 | .env 86 | .venv 87 | env/ 88 | venv/ 89 | ENV/ 90 | env.bak/ 91 | venv.bak/ 92 | 93 | # Spyder project settings 94 | .spyderproject 95 | .spyproject 96 | 97 | # Rope project settings 98 | .ropeproject 99 | 100 | # mkdocs documentation 101 | /site 102 | 103 | # mypy 104 | .mypy_cache/ 105 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Vechicle-Routing-Problem-VRP-with-Pickup-and-Delivery 2 | Pickup-and-Delivery Problems (PDPs) constitute an important family of routing problems in which goods or passengers have to be transported from different origins to different destinations. These problems are usually defined on a graph in which vertices represent origins or destinations for the different entities (or commodities) to be transported. PDPs can be classified into three main categories according to the type of demand and route structure being considered. In many-to-many (M-M) problems, each commodity may have multiple origins and destinations and any location may be the origin or destination of multiple commodities. These problems arise, for example, in the repositioning of inventory between retail stores or in the management of bicycle or car sharing systems. One-tomany- to-one (1-M-1) problems are characterized by the presence of some commodities to be delivered from a depot to many customers and of other commodities to be collected at the customers and transported back to the depot. These have applications, for example, in the distribution of beverages and the collection of empty cans and bottles. They also arise in forward and reverse logistics systems where, in addition to delivering new products, one must plan the collection of used, defective, or obsolete products. Finally, in one-to-one (1-1) problems, each commodity has a single origin and a single destination between which it must be transported. Typical applications of these problems are less than- truckload transportation and urban courier operations. 3 | -------------------------------------------------------------------------------- /pickup and delivery.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ShadowOS/Vechicle-Routing-Problem-VRP-with-Pickup-and-Delivery/f634e334542adacf31ebbb05a56f615e60bde80d/pickup and delivery.xlsx -------------------------------------------------------------------------------- /vrppnd.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Mon May 13 23:10:18 2019 4 | 5 | @author: ANUDEEP AKKANA 6 | """ 7 | 8 | 9 | from gurobipy import* 10 | import os 11 | import xlrd 12 | 13 | book = xlrd.open_workbook(os.path.join("pickup and delivery.xlsx")) 14 | 15 | 16 | 17 | Node=[] 18 | Demand={} #Demand in Thousands 19 | Distance={} #Distance in kms 20 | VehicleNum=[] #Vehicle number 21 | 22 | 23 | 24 | 25 | sh = book.sheet_by_name("Demand") 26 | i = 1 27 | while True: 28 | try: 29 | sp = sh.cell_value(i,0) 30 | Node.append(sp) 31 | Demand[sp]=sh.cell_value(i,1) 32 | i = i + 1 33 | except IndexError: 34 | break 35 | 36 | sh = book.sheet_by_name("VehicleNum") 37 | 38 | i = 1 39 | while True: 40 | try: 41 | sp = sh.cell_value(i,0) 42 | VehicleNum.append(sp) 43 | i = i + 1 44 | except IndexError: 45 | break 46 | cost={} 47 | sh = book.sheet_by_name("Cost") 48 | i = 1 49 | for P in Node: 50 | j = 1 51 | for Q in Node: 52 | cost[P,Q] = sh.cell_value(i,j) 53 | j += 1 54 | i += 1 55 | sh = book.sheet_by_name("Distance") 56 | i = 1 57 | for P in Node: 58 | j = 1 59 | for Q in Node: 60 | Distance[P,Q] = sh.cell_value(i,j) 61 | j += 1 62 | i += 1 63 | Aij = {} 64 | sh = book.sheet_by_name("Aij") 65 | i = 1 66 | for P in Node: 67 | j = 1 68 | for Q in Node: 69 | Aij[P,Q] = sh.cell_value(i,j) 70 | j += 1 71 | i += 1 72 | 73 | numberOfVehicle=2 74 | 75 | K=numberOfVehicle 76 | 77 | m=Model("Pick_up_and_Delivery") 78 | 79 | 80 | m.modelSense=GRB.MINIMIZE 81 | Q = 20 #vehicle capacity 82 | xijk=m.addVars(Node,Node,VehicleNum,vtype=GRB.BINARY,name='X_ijk') 83 | fij=m.addVars(Node,Node,vtype=GRB.INTEGER,name='f_ijk') 84 | #Uik=m.addVars(Node,VehicleNum,vtype=GRB.CONTINUOUS,name='Uik') 85 | 86 | 87 | m.setObjective(sum((cost[i,j]*xijk[i,j,k] for i in Node for j in Node for k in VehicleNum if Aij[i,j] == 1))) 88 | 89 | for i in Node : 90 | if i!='Depot': 91 | m.addConstr(sum(xijk[i,j,k] for j in Node for k in VehicleNum if Aij[i,j] == 1)==1) 92 | 93 | for i in Node: 94 | for k in VehicleNum: 95 | m.addConstr(sum(xijk[i,j,k] for j in Node if Aij[i,j] == 1)-sum(xijk[j,i,k] for j in Node if Aij[i,j] == 1)==0) 96 | 97 | for i in Node: 98 | if i!= 'Depot': 99 | m.addConstr(sum(fij[j,i] for j in Node if Aij[i,j] == 1)-sum(fij[i,j] for j in Node if Aij[i,j] == 1) == Demand[i] ) 100 | for i in Node: 101 | for j in Node: 102 | m.addConstr(fij[i,j]>=0) 103 | for i in Node: 104 | for j in Node: 105 | if Aij[i,j] == 1: 106 | m.addConstr((Q*(sum(xijk[i,j,k] for k in VehicleNum)))>=fij[i,j]) 107 | 108 | for i in Node: 109 | for j in Node: 110 | if(i!='Depot'): 111 | if(j!='Depot'): 112 | m.addConstr(sum(xijk[i,j,k] for k in VehicleNum)<=4) 113 | 114 | 115 | 116 | m.write('Pickupanddelivery.lp') 117 | 118 | m.optimize() 119 | 120 | for v in m.getVars(): 121 | if v.x > 0.01: 122 | print(v.varName, v.x) 123 | print('Objective:',m.objVal) --------------------------------------------------------------------------------