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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics
Jose Alejandro Cano
Universidad de Medellín
Computer Science & IT Electrical & Electronics Engineering

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Solving the order batching and sequencing problem with multiple pickers: A grouped genetic algorithm Jose Alejandro Cano; Pablo Cortés; Emiro Antonio Campo; Alexander Alberto Correa-Espinal
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2516-2524

Abstract

This paper introduces a grouped genetic algorithm (GGA) to solve the order batching and sequencing problem with multiple pickers (OBSPMP) with the objective of minimizing total completion time. To the best of our knowledge, for the first time, an OBSPMP is solved by means of GGA considering picking devices with heterogeneous load capacity. For this, an encoding scheme is proposed to represent in a chromosome the orders assigned to batches, and batches assigned to picking devices. Likewise, the operators of the proposed algorithm are adapted to the specific requirements of the OBSPMP. Computational experiments show that the GGA performs much better than six order batching and sequencing heuristics, leading to function objective savings of 18.3% on average. As a conclusion, the proposed algorithm provides feasible solutions for the operations planning in warehouses and distribution centers, improving margins by reducing operating time for order pickers, and improving customer service by reducing picking service times.
Improving cross-docking operations for consumer goods sector using metaheuristics Rodrigo Andrés Gómez- Montoya; Jose Alejandro Cano; Emiro Antonio Campo; Fernando Salazar
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2710

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 cross-docking 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. 
Formulations for joint order picking problems in low-level picker-to-part systems Jose Alejandro Cano
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (411.409 KB) | DOI: 10.11591/eei.v9i2.2110

Abstract

This article introduces several mathematical formulations for the joint order picking problem (JOPP) in low-level picker-to-part warehousing systems. In order to represent real warehousing environments, the proposed models minimize performance measures such as travel distance, travel time and tardiness, considering multi-block warehouses, due dates, and multiple pickers. The number of constraints and decision variables required for each proposed model is calculated, demonstrating the complexity of solving medium and long-sized problems in reasonable computing time using exact methods. The proposed models can be followed as a reference for new solution methods that yield efficient and fast solutions.
Co-Authors Alexander Alberto Correa-Espinal Emiro Antonio Campo Emiro Antonio Campo Fernando Salazar Pablo Cortés Rodrigo Andrés Gómez- Montoya