Ne Network D k Des esign F ign For M Mid id-da day y Me Meal Prog ogram Priyanka Singh | Afsaruzzaman Noor Capstone Project Adviser: Tim Russell 1
Ov Overvie iew of Ak Akshaya Pa Patra The World's Largest NGO-Run Mid-Day Meal Program Serving Wholesome School Lunch to Over 1.7 Million Children in 14,173 Schools Across 12 States in India. 2
Ak Akshaya Patra Video 3
Pr Problem State atement What would be the optimal centralized kitchens network design for Akshaya Patra to serve all the public schools of UP? 4
Ge Geographic Sc c Scope 5
Wh Why th the p e projec ect is t is s sig ignif ific ican ant t Growing demand of mid-day meal Number of children served in UP 10 9.4M* state = 0.21M NO. OF CHILDREN (IN 8.4M 8 Minimum cost to open one 6.7M MILLIONS) 6 centralized kitchen is 10M INR. 4 Capacity of centralized kitchen is 2 250,000 meals 0 2008 2016 2020 6
Cu Current Supply chain proc ocess 7
Ki Kitchens Centralized kitchens Decentralized kitchens 8
Literature Review • Perishability challenge • Harvard case study • Optimization • Food delivery • Cross docking 9
Cr Cros oss doc ocking Block Block Block Cross docking Point (loading/unloading zone) Delivery in large truck Block with capacity 9000 kg Centralized Kitchen Block Food delivery to blocks and then schools in mid-size truck with capacity 900 kg 10
Me Method odol olog ogy Interview with Locate Analyze Formulate Test various Akshaya Patra potential sites current supply model scenarios and collect of centralized chain utilizing MILP data kitchens 11
Pr Problem Formulat ation - Candidate locations for kitchens and cross docking facilities 66 cities within Uttar Pradesh - Customers 1076 blocks (157 schools on average with 50 kids in each school) - Data 66 by 1076 matrix each for distance and time (each city to each block) Goal: MINIMIZE Kitchen set up cost + Delivery cost Subject to Constraints- Demand, Supply, Time, Co-location, Flow conservation 12
Me Method odol olog ogy…. Va Various Scenarios For Network design 1. Network design without capacity constraint 2. Network design with capacity constraint 3. Network design with insulated containers 4. Network design considering currently opened kitchens 5. Network design with cross docking and capacity constraint 6. Network design with cross docking and insulated containers 13
Cos Cost analysis for or on one year (a (all sc scenarios) s) Fi Fixed cost (up Tr Transportation cost (1 day)- On One year total cost- Scen Sc enarios Network Designs Ne fr front)-a a (INR) b b (INR) a + b*225 (I a (INR NR) Without capacity Sc Scen enario 1 100,000,000 6,296,264 1,516,659,400 constraint Sc Scen enario 2 With capacity constraint 370,000,000 3,280,810 1,108,182,250 Sc Scen enario 3 With insulated containers 360,000,000 4,590,560 1,392,876,000 Considering currently Sc Scen enario 4 370,000,000 3,297,892 1,112,025,700 opened kitchens With Cross docking and Scen Sc enario 5 380,000,000 2,969,716 1,048,186,100 capacity constraint With Cross docking and Sc Scen enario 6 370,000,000 2,763,304 991,743,400 insulated containers 14
Cos Cost analysis for or on one year (G (Graph) 15
Cos Cost analysis for or on one year (a (all sc scenarios) s) Fi Fixed cost (up Tr Transportation cost (1 day)- On One year total cost- Scen Sc enarios Network Designs Ne fr front)-a a (INR) b b (INR) a + b*225 (I a (INR NR) Without capacity Sc Scen enario 1 100,000,000 6,296,264 1,516,659,400 constraint Sc Scen enario 2 With capacity constraint 370,000,000 3,280,810 1,108,182,250 Sc Scen enario 3 With insulated containers 360,000,000 4,590,560 1,392,876,000 Considering currently Sc Scen enario 4 370,000,000 3,297,892 1,112,025,700 opened kitchens With Cross docking and Scen Sc enario 5 380,000,000 2,969,716 1,048,186,100 capacity constraint With Cross docking and Sc Scen enario 6 370,000,000 2,763,304 991,743,400 insulated containers 16
Co Cost t analysis for r fiv five years (Mo (Model el consider ers upfr front t cost t and 1 day del eliver ery cost) t) Fi Fixed cost (up Transportation cost (1 day)- Tr Fi Five year total cost- Sce Scenarios Network Desig Ne igns ns fr fron ont)-a a (INR NR) b b (INR NR) a+ a+b*225* 225*5 5 (I (INR) With capacity Sce Scenario 2 370,000,000 3,280,810 4,060,911,250 constraint With insulated Sce Scenario 3 360,000,000 4,590,560 5,524,380,000 containers With Cross docking Scenario 5 Sce and capacity 380,000,000 2,969,716 3,720,930,500 constraint With Cross docking Sce Scenario 6 and insulated 370,000,000 2,763,304 3,478,717,000 containers 17
Cos Cost analysis for or five years (Mo Model el consider ers upfr front t cost t and 1 day del eliver ery cost) 18
Co Cost t analysis for r fiv five years (Mo (Model el consider ers upfr front t cost t divided ed by 5 and 1 yea ear del eliver ery cost) t) Fixed cost for 1 st year (up Transportation cost Five year total Scenarios Network Designs front by five)- (1 year)- cost- a+b*5 (INR) a (INR) b (INR) With capacity Scenario 2 590,000,000 619,006,050 3,685,030,250 constraint With insulated Scenario 3 590,000,000 618,988,500 3,684,942,500 containers With Cross docking Scenario 5 and capacity 420,000,000 632,166,602 3,580,833,010 constraint With Cross docking Scenario 6 and insulated 420,000,000 604,595,507 3,442,977,535 containers 19
Cos Cost analysis for or five years (Mo (Model el consider ers upfr front t co cost divided by 5 and 1 year delive very co cost) 20
Five Fiv e year ears’ cost t compar paris ison Five year cost analysis (in INR) 5 years Total cost 5 years Total cost No. of ( Model considers No. of Network designs scenarios ( Model considers Kitchens upfront cost Kitchens upfront cost and 1 opened divided by 5 and 1 opened day delivery cost ) year delivery cost ) With capacity constraint 4,060,911,250 37 3,685,030,250 59 With insulated containers 5,524,380,000 36 3,684,942,500 59 With Cross docking and 3,720,930,500 38 3,580,833,010 42 capacity constraint With Cross docking and 3,478,717,000 37 3,442,977,535 42 insulated containers 21
Fiv Five e year ears’ cost t compar paris ison 22
Li Limitations - Truck Size - Truck Utilization (36% are under utilized) - Decentralized kitchen - Cross docking cost - Cost of insulated containers - Cost of inbound transportation - Cost of setting up kitchens in different locations 23
Con Conclusion on From our analysis, we found that investing in - insulated containers (increasing the food serving time limit from four to six hours) along with - consolidated deliveries within cities provides the most attractive solution (Scenario 6)* * Remember the model considers upfront fixed cost and 1 day of delivery cost 24
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