Intelligent Warehouse Picking Improvement Model for e-Logistics Warehouse Using Single Picker Routing Problem and Wave Picking

Dida Diah Damayanti - Telkom University, Bandung,40257, Indonesia
Nia Novitasari - Telkom University, Bandung,40257, Indonesia
Erlangga Bayu Setyawan - Telkom University, Bandung,40257, Indonesia
Prafajar Suksessanno Muttaqin - Telkom University, Bandung,40257, Indonesia


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DOI: http://dx.doi.org/10.30630/joiv.6.2.1006

Abstract


Abstract— The development and use of technological innovations have changed people's behavior from an industrial society to an information society. It can be seen in the increase in people's consumption patterns from trading through physical stores (offline) to trading through electronic systems, often referred to as e-commerce. Logistics services are distribution actors in the downstream line which are tasked with delivering products from the fulfillment center from e-commerce to the end customer. The uncertainty of the number of requests is the biggest challenge for logistics service players. The growth of e-commerce has also led to an increase in sales volume in e-commerce which has given rise to a new generation of warehouses that are specifically tailored to the special needs of online retailers who directly serve the demands of end-customers in the business-to-consumer (B2C) segment. Traditional warehousing systems cannot handle orders with the characteristics of many transactions but smaller sizes. In addition, warehouses that handle e-commerce are also required to have a fast process in the warehouse because shipments must be made on the same day. In this study, the author aims to perform calculations to find the optimal order picking time in the warehouse, so orders in e-commerce can be processed faster by comparing the picking process time using ordinary Single Picker Routing Problem (SPRP) and combined with the concept of wave picking using Genetic Algorithm (GA). Based on a theoretical study in this paper, the combination between SPRP and wave picking can reduce 42.28% picking time.

 


Keywords


e-commerce; intelligent warehouse; order picking; wave picking; Single Picker Routing Problem (SPRP), logistic

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