Improving cross-docking operations for consumer goods sector using metaheuristics

Rodrigo Andrés Gómez-Montoya, Jose Alejandro Cano, Emiro Antonio Campo, Fernando Salazar

Research output: Contribution to journalArticlepeer-review

Abstract

This paper aims to model a consumer goods cross-docking problem, which is solved using metaheuristics to minimize makespan and determine the capacity in terms of inbound and outbound docks. The consumer-goods cross-docking problem is represented through inbound and outbound docks, customer orders (products to be delivered to customers), and metaheuristics as a solution method. Simulated annealing (SA) and particle swarm optimization (PSO) are implemented to solve the cross-docking problem. Based on the results of statistical analysis, it was identified that the two-way interaction effect between inbound and outbound docks, outbound docks and items, and items and metaheuristics are the most statistically significant on the response variable. The best solution provides the minimum makespan of 973.42 minutes considering nine inbound docks and twelve outbound docks. However, this study detected that the combination of six inbound docks and nine outbound docks represents the most efficient solution for a crossdocking design since it reduces the requirement of docks by 28.6% and increases the makespan by only 4.2% when compared to the best solution, representing a favorable trade-off for the cross-docking platform design.

Original languageEnglish
Pages (from-to)524-532
Number of pages9
JournalBulletin of Electrical Engineering and Informatics
Volume10
Issue number1
DOIs
StatePublished - Feb 2021

Keywords

  • Consumer goods sector
  • Cross-docking
  • Distribution center
  • Particle swarm optimization
  • Simulated annealing

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