Milliken lagrange isye 6203 project evaluation of consolidation strategy for ltl shipments
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Milliken Lagrange ISYE 6203 PROJECT “Evaluation of Consolidation Strategy for LTL Shipments”. Chunhao GAO Halil Ozan GOZBASI Hashai PAPNEJA Jin SHI Lin WAN Jie ZHU. Company Overview. Textile Manufacturing Industry Produces finished fabrics for rugs and carpets

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Milliken Lagrange ISYE 6203 PROJECT “Evaluation of Consolidation Strategy for LTL Shipments”

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Milliken lagrange isye 6203 project evaluation of consolidation strategy for ltl shipments

Milliken LagrangeISYE 6203 PROJECT“Evaluation of Consolidation Strategy for LTL Shipments”

Chunhao GAO

Halil Ozan GOZBASI

Hashai PAPNEJA

Jin SHI

Lin WAN

Jie ZHU


Company overview

Company Overview

  • Textile Manufacturing Industry

  • Produces finished fabrics for rugs and carpets

  • Synthetic fabrics used in such goods as apparel, automobiles, tennis balls, and specialty textiles

  • Milliken operates more than 60 plants worldwide


Project topic

Project Topic

  • Evaluation of consolidation option for Less-Than-Truckload (LTL) shipments

  • Plant in Lagrange,GA

  • Customers, almost every state in USA


Less than truckload vs ftl consolidation

Less-Than-Truckloadvs.FTL Consolidation

Customer 1

  • Small shipments

  • Send Directly from Plant to Customers

LTL

LTL

DC

FTL

Customer 2

LTL

Plant

LTL


Solution approach

Solution Approach

  • Data Analysis

    • Cost Structure

      • Parcel, LTL, FTL

    • Aggregating Customers

      • 3-Zip Customers (30332, 30345, 30358)-> 303)

    • Reduce Number of Customers

      • Focus on customers which constitute 90% of the transportation cost


Data analysis cost structure

Data Analysis- Cost Structure

Consolidation Strategy to decrease LTL costs


Data analysis aggregation

Data Analysis - Aggregation

Number of 3-Zip Customers: 792

90% Tail : 325

Size reduced by ~60%


Mapping the demand by total freight

Mapping the Demand by Total Freight


Mapping the demand by total trucks

Mapping the Demand by Total Trucks


Candidate dc selection

Candidate DC Selection


Model building

Model Building

  • Parameters


Model building1

Model Building

  • Decision Variables


Objective constraints

Objective & Constraints


Parameter estimation

Parameter Estimation

  • CZARLITE LTL Pricing Software

  • Prices from each candidate DC to every 3-digit customer region which are closer than 700 miles.

  • For numerical comparability

    We have real LTL from Plant to Customers

    Discount_Rate= Real_LTL_Cost / CZARLITE LTL Cost

    Update all prices by

    LTL(model) Cost= CZARLITE LTL Cost* Discount_Rate


Results

Results

Benefits from Consolidation Strategy is Related to Frequency


Frequency consolidation

Frequency & Consolidation

  • Low frequency increases consolidation of loads into each truck

  • Less number of trucks are used in consolidation


Frequency 3

Frequency 3:


Frequency 3 ltl from plant

Frequency 3: LTL from Plant


Frequency 3 dc1 in nc

Frequency 3: DC1 in NC


Frequency 3 dc2 in al

Frequency 3: DC2 in AL


Frequency 3 dc3 in ca

Frequency 3: DC3 in CA


Implementation

Implementation

  • First Approach:

    • Ship from Plant to DC`s in a pre-agreed frequency-regardless of the loads

  • Second Approach:

    • Estimate a Threshold Level for each DC

    • Check accumulated shipments

      • If total load is greater than Threshold

        • Send a Full Truck to DC

    • Else

      • LTL to customer from Plant


Conclusion future work

Conclusion & Future Work

  • Develop implementation techniques

    • Estimation of Threshold Levels

  • Take more product types into consideration (such as chemicals)

  • Try to use LTL rates from current carriers instead of Czarlite for a more accurate model solution

  • Consider other costs related to consolidation

    • DC space cost

    • Material Handling cost


Thanks

Thanks..

  • Milliken Company

  • Prof. Vande Vate


Additional slides

Additional Slides


Frequency 2 ltl from plant

Frequency 2: LTL from Plant


Frequency 2 dc1 in nc

Frequency 2: DC1 in NC


Frequency 2 dc2 in al

Frequency 2: DC2 in AL


Frequency 1 dc3 in ca

Frequency 1: DC3 in CA


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