A simulation-optimization framework for cross-docking assignment problem

Research output: Contribution to conferencePaper

Abstract

This paper presents a hybrid simulation-optimization framework for cross-docking assignment problem in order fulfillment systems. Orders are assigned to inbound docks, processed in production lines, and then distributed to either domestic or international destinations. An optimization model is used to assign the trucks and orders to the inbound and outbound docks by minimizing the total cost. A discrete-event simulation model is used to account for the uncertainty and variations in the system. Processing times of the orders and truck and pallet assignments are modified based on the result of the simulation model and send back to the optimization model. Orders priorities in the optimization model are adjusted iteratively until convergence is achieved. The proposed framework provides a real-time scheduling for customer orders and available resources while considering the dynamic changes in the system. The framework is demonstrated through a case study from an electronics manufacturing company.

Original languageEnglish (US)
Pages1864-1869
Number of pages6
StatePublished - 2020
Event2016 Industrial and Systems Engineering Research Conference, ISERC 2016 - Anaheim, United States
Duration: May 21 2016May 24 2016

Conference

Conference2016 Industrial and Systems Engineering Research Conference, ISERC 2016
CountryUnited States
CityAnaheim
Period5/21/165/24/16

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

Fingerprint Dive into the research topics of 'A simulation-optimization framework for cross-docking assignment problem'. Together they form a unique fingerprint.

  • Cite this

    Aqlan, F., & Ashour, O. (2020). A simulation-optimization framework for cross-docking assignment problem. 1864-1869. Paper presented at 2016 Industrial and Systems Engineering Research Conference, ISERC 2016, Anaheim, United States.