Comparação através do picking em loja de duas alternativas de entrega em um ambiente de entrega em domicílios em supermercados. Área temática: logística na cidade
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May 31, 2017
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Resumo
Na Colômbia, o comercio eletrônico vem acrescentando consideravelmente segundo cifras da Câmara Colombiana de Comercio Eletrônico, CCCE. Neste mercado, as grandes superfícies como Jumbo, La 14, Almacenes
Éxito e Carulla, entre outras, participam através do serviço de entregas em domicílio (Home delivery). Este serviço compõe-se de três etapas principais que começam com a recepção do pedido, continuam com a coleta na loja dos produtos que compõem a ordem (order picking) e acabam com a entrega ao freguês (delivery). A eficiência nos processos
logísticos é essencial para garantir a rentabilidade dos supermercados neste segmento. Em particular, a etapa de order picking é fundamental, já que representa cerca da metade dos custos de armazenagem. Enquadrado no processo picking em loja, este documento apresenta e analisa a comparação de duas alternativas de entrega de produtos:
i) durante o mesmo dia, ii) no dia seguinte. No primeiro caso, os pedidos são processados quando eles chegar, seguindo o critério FIFO (first in first out) para a assinação de cada ordem a cada operário. No segundo caso, as ordens são acumuladas e despachadas o dia seguinte, o que permite
agrupá-las em lotes (batching) e assignar a cada operário um ou vários lotes para realizar o picking. Essas duas alternativas foram comparadas utilizando simulação por eventos discretos. Os resultados indicaram que suster ao cliente a promessa de entrega durante o mesmo dia de colocação do pedido incrementa os custos operacionais de picking em
450% na média.
Éxito e Carulla, entre outras, participam através do serviço de entregas em domicílio (Home delivery). Este serviço compõe-se de três etapas principais que começam com a recepção do pedido, continuam com a coleta na loja dos produtos que compõem a ordem (order picking) e acabam com a entrega ao freguês (delivery). A eficiência nos processos
logísticos é essencial para garantir a rentabilidade dos supermercados neste segmento. Em particular, a etapa de order picking é fundamental, já que representa cerca da metade dos custos de armazenagem. Enquadrado no processo picking em loja, este documento apresenta e analisa a comparação de duas alternativas de entrega de produtos:
i) durante o mesmo dia, ii) no dia seguinte. No primeiro caso, os pedidos são processados quando eles chegar, seguindo o critério FIFO (first in first out) para a assinação de cada ordem a cada operário. No segundo caso, as ordens são acumuladas e despachadas o dia seguinte, o que permite
agrupá-las em lotes (batching) e assignar a cada operário um ou vários lotes para realizar o picking. Essas duas alternativas foram comparadas utilizando simulação por eventos discretos. Os resultados indicaram que suster ao cliente a promessa de entrega durante o mesmo dia de colocação do pedido incrementa os custos operacionais de picking em
450% na média.
Keywords
delivery, order picking, lot creation, discrete event simulationEntrega a domicilio, coleta de produtos, criação de lotes, simulação por eventos discretosEntrega a domicilio, recolección de productos, creación de lotes, simulación por eventos discretos.
References
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Bartholdi, John J. & Eisenstein, Donald D. (1996). A Production Line that Balance Itself. Operations Research, 44 (1), Special Issue on New Directions in Operations Management, 21-34.
Boyer, Kenneth K. & Hult, G. Thomas M. (2006). Customer Behavioral Intentions for Online Purchases: An Examination of Fulfillment Method and Customer Experience Level. Journal of Operations
Management, 24 (2), 124-147. http://doi.org/10.1016/j.jom.2005.04.002
Bühler, Dominic; Klein, Robert & Neugebauer, Michael (2016). Model-Based Delivery Cost Approximation in Attended Home Services. Computers & Industrial Engineering, 98 (C), 78-90. http://doi.org/10.1016/j.cie.2016.05.014
Cámara Colombiana de Comercio Electrónico, CCCE (2016). Estudio Observatorio de compra online – Segunda oleada, Colombia 2016. Bogotá. Disponible en: https://www.ccce.org.co/sites/default/files/biblioteca/Infograf%C3%ADa%20.pdf
Chen, Yi-zhou; Shen, Shi Fei; Chen, Tao & Yang, Rui (2014). Path Optimization Study for Vehicles Evacuation Based on Dijkstra Algorithm. Procedia Engineering, 71, 159-165. http://doi.org/10.1016/j.proeng.2014.04.023.Disponible en: https://www.researchgate.net/publication/262769062_Path_Optimization_Study_for_Vehicles_Evacuation_based_on_Dijkstra_Algorithm
Duin, J. H. Ron van; Goffau, Wim de; Wiegmans, Bart; Tavasszy, Lori A. & Saes, Maurice (2016). Improving Home Delivery Efficiency by Using Principles of Address Intelligence for B2C Deliveries.
Transportation Research Procedia, 12, 14-25. http://doi.org/10.1016/j.trpro.2016.02.006. Disponible en: http://repository.tudelft.nl/islandora/object/uuid%3Aa2f956b9-57ad-4f41-ad09-df318acf7234
Durand, Bruno & González-Feliu, Jesús (2012). Urban Logistics and E-Grocery: Have Proximity Delivery Services a Positive Impact on Shopping Trips? Procedia – Social and Behavioral Sciences, 39, 510-520. http://doi.org/10.1016/j.sbspro.2012.03.126
Ehmke, Jan Fabian & Campbell, Ann Melissa (2014). Customer Acceptance Mechanisms for Home Deliveries in Metropolitan Areas. European Journal of Operational Research, 233 (1), 193-207. http://doi.org/10.1016/j.ejor.2013.08.028. Disponible en: https://www.researchgate.net/profile/
Ann_Campbell4/publication/270992093_Customer_acceptance_mechanisms_for_home_deliveries_in_metropolitan_areas/links/561e607208aef097132c1b49/Customer-acceptance-mechanisms-forhome-deliveries-in-metropolitan-areas.pdf
Hall, Randolph W. (1993). Distance Approximations for Routing Manual Pickers in a Warehouse. IIE
Transactions, 25 (4), 76-87. http://doi.org/10.1080/07408179308964306
Henn, Sebastian & Wäscher, Gerhard (2012). Tabu Search Heuristics for the Order Batching Problem in Manual Order Picking Systems. European Journal of Operational Research, 222 (3), 484-494. http://doi.
org/10.1016/j.ejor.2012.05.049
Hong, Soondo; Johnson, Andrew L. & Peters, Brett A. (2012). Batch Picking in Narrow-Aisle Order Picking Systems with Consideration for Picker Blocking. European Journal of Operational Research, 221 (3), 557-570. http://doi.org/10.1016/j.ejor.2012.03.045. Disponible en: https://www.researchgate.net/
publication/257196172_Batch_picking_in_narrow-aisle_order_picking_systems_with_consideration_for_picker_blocking
Hong, Soondo & Kim, Youngjoo (2017). A Route-Selecting Order Batching Model with the S-Shape Routes in a Parallel-Aisle Order Picking System. European Journal of Operational Research, 257 (1), 185-196.http://doi.org/10.1016/j.ejor.2016.07.017
Hsu, Chih-Ming; Chen, Kai-Ying & Chen, Mu-Chen (2005). Batching Orders in Warehouses by Minimizing Travel Distance with Genetic Algorithms. Computers in Industry, 56 (2), 169-
178. http://doi.org/10.1016/j.compind.2004.06.001
Hwang, Heung Suk & Cho, Gyu Sung (2006). A Performance Evaluation Model for Order Picking Warehouse Design. Computers and Industrial Engineering, 51 (2), 335-342.
http://doi.org/10.1016/j.cie.2005.10.002
Javelin Group (2011). How Many Stores Will We Really Need? UK Non-Food Retailing in 2020. Disponible en: http://www.javelingroup. com/white_paper/white_paper_registration_how_many_stores/
Koo, Pyung-Hoi (2009). The Use of Bucket Brigades in Zone Order Picking Systems. OR Spectrum, 31 (4), 759-774. http://doi.org/10.1007/s00291-008-0131-x
Koster, René de (1994). Performance Approximation of Pick-To-Belt Order Picking Systems. European Journal of Operational Research, 72 (3), 558-573. http://doi.org/10.1016/0377-2217(94)90423-5. Disponible en: https://repub.eur.nl/pub/11836/PerformanceApproximation_1994pdf.pdf
Koster, René de; Le-Duc, Tho & Roodbergen, Kees Jan (2007). Design and Control of Warehouse Order Picking: A Literature Review. European Journal of Operational Research, 182 (2), 481-501. http://doi.
org/10.1016/j.ejor.2006.07.009. Disponible en: http://roodbergen.com/publications/EJOR2007.pdf
Le-Duc, Tho & Koster, René de (2007). Travel Time Estimation and Order Batching in a 2-Block Warehouse. European Journal of Operational Research, 176 (1), 374-388.
http://doi.org/10.1016/j.ejor.2005.03.052
Liao, Shu-hsien; Chen, Yin-ju & Lin, Yi-tsun (2011). Mining Customer Knowledge to Implement Online Shopping and Home Delivery for Hypermarkets. Expert Systems with Applications, 38 (4), 3982-3991.
http://doi.org/10.1016/j.eswa.2010.09.059. Disponible en: ftp://140.131.110.38/leecc/public/SPSS&AppofStatistics/2011Papers/Reference/Mining%20customer%20knowledge%20to%20implement%20online%20shopping%20and%20home%20delivery%20for%20hypermarkets.pdf
Martello, Silvano & Toth, Paolo (1987). Algorithms for Knapsack Problems. North- Holland Mathematics Studies, 132 (C), 213-257. http://doi.org/10.1016/S0304-0208(08)73237-7
Pan, Jason Chao-Hsien; Shih, Po-Hsun & Wu, Ming-Hung (2015). Order Batching in a Pick-and-Pass Warehousing System with Group Genetic Algorithm. Omega, 57, 238-248. http://doi.org/10.1016/j.
omega.2015.05.004
Park, Minyoung & Regan, Amelia (2004). Issues in Emerging Home Delivery Operations. University of California Transportation Center, 2 (2), 1-13. http://doi.org/10.1068/a201285
Rincón-García, Nicolás (2016). Freight Transport, Routing Software and Time- Dependent Vehicle Routing Models. Doctoral Thesis. University of Southampton, Faculty of Engineering and the Environment, Southampton, England. Disponible en: https://eprints.soton.ac.uk/397141/1/FINAL%2520ETHESIS%2520FOR%2520EPRINTS%252025739344.pdf
Saskia, Seidel; Mareï, Nora & Blanquart, Corinne (2016). Innovations in e-Grocery and Logistics olutions for Cities. Transportation Research Procedia, 12, 825-835. http://doi.org/10.1016/j.trpro.2016.02.035
Visser, Johan; Nemoto, Toshinori & Browne, Michael (2014). Home Delivery and the Impacts on Urban Freight Transport: A Review. Procedia - Social and Behavioral Sciences, 125, 15-27. http://doi.org/10.1016/j.sbspro.2014.01.1452
Yu, Mengfei & Koster, René de (2010). Enhancing Performance in Order Picking Processes by Dynamic Storage Systems. International Journal of Production Research, 48 (16), 4785-4806. http://doi.
org/10.1080/00207540903055693
Bartholdi, John J. & Eisenstein, Donald D. (1996). A Production Line that Balance Itself. Operations Research, 44 (1), Special Issue on New Directions in Operations Management, 21-34.
Boyer, Kenneth K. & Hult, G. Thomas M. (2006). Customer Behavioral Intentions for Online Purchases: An Examination of Fulfillment Method and Customer Experience Level. Journal of Operations
Management, 24 (2), 124-147. http://doi.org/10.1016/j.jom.2005.04.002
Bühler, Dominic; Klein, Robert & Neugebauer, Michael (2016). Model-Based Delivery Cost Approximation in Attended Home Services. Computers & Industrial Engineering, 98 (C), 78-90. http://doi.org/10.1016/j.cie.2016.05.014
Cámara Colombiana de Comercio Electrónico, CCCE (2016). Estudio Observatorio de compra online – Segunda oleada, Colombia 2016. Bogotá. Disponible en: https://www.ccce.org.co/sites/default/files/biblioteca/Infograf%C3%ADa%20.pdf
Chen, Yi-zhou; Shen, Shi Fei; Chen, Tao & Yang, Rui (2014). Path Optimization Study for Vehicles Evacuation Based on Dijkstra Algorithm. Procedia Engineering, 71, 159-165. http://doi.org/10.1016/j.proeng.2014.04.023.Disponible en: https://www.researchgate.net/publication/262769062_Path_Optimization_Study_for_Vehicles_Evacuation_based_on_Dijkstra_Algorithm
Duin, J. H. Ron van; Goffau, Wim de; Wiegmans, Bart; Tavasszy, Lori A. & Saes, Maurice (2016). Improving Home Delivery Efficiency by Using Principles of Address Intelligence for B2C Deliveries.
Transportation Research Procedia, 12, 14-25. http://doi.org/10.1016/j.trpro.2016.02.006. Disponible en: http://repository.tudelft.nl/islandora/object/uuid%3Aa2f956b9-57ad-4f41-ad09-df318acf7234
Durand, Bruno & González-Feliu, Jesús (2012). Urban Logistics and E-Grocery: Have Proximity Delivery Services a Positive Impact on Shopping Trips? Procedia – Social and Behavioral Sciences, 39, 510-520. http://doi.org/10.1016/j.sbspro.2012.03.126
Ehmke, Jan Fabian & Campbell, Ann Melissa (2014). Customer Acceptance Mechanisms for Home Deliveries in Metropolitan Areas. European Journal of Operational Research, 233 (1), 193-207. http://doi.org/10.1016/j.ejor.2013.08.028. Disponible en: https://www.researchgate.net/profile/
Ann_Campbell4/publication/270992093_Customer_acceptance_mechanisms_for_home_deliveries_in_metropolitan_areas/links/561e607208aef097132c1b49/Customer-acceptance-mechanisms-forhome-deliveries-in-metropolitan-areas.pdf
Hall, Randolph W. (1993). Distance Approximations for Routing Manual Pickers in a Warehouse. IIE
Transactions, 25 (4), 76-87. http://doi.org/10.1080/07408179308964306
Henn, Sebastian & Wäscher, Gerhard (2012). Tabu Search Heuristics for the Order Batching Problem in Manual Order Picking Systems. European Journal of Operational Research, 222 (3), 484-494. http://doi.
org/10.1016/j.ejor.2012.05.049
Hong, Soondo; Johnson, Andrew L. & Peters, Brett A. (2012). Batch Picking in Narrow-Aisle Order Picking Systems with Consideration for Picker Blocking. European Journal of Operational Research, 221 (3), 557-570. http://doi.org/10.1016/j.ejor.2012.03.045. Disponible en: https://www.researchgate.net/
publication/257196172_Batch_picking_in_narrow-aisle_order_picking_systems_with_consideration_for_picker_blocking
Hong, Soondo & Kim, Youngjoo (2017). A Route-Selecting Order Batching Model with the S-Shape Routes in a Parallel-Aisle Order Picking System. European Journal of Operational Research, 257 (1), 185-196.http://doi.org/10.1016/j.ejor.2016.07.017
Hsu, Chih-Ming; Chen, Kai-Ying & Chen, Mu-Chen (2005). Batching Orders in Warehouses by Minimizing Travel Distance with Genetic Algorithms. Computers in Industry, 56 (2), 169-
178. http://doi.org/10.1016/j.compind.2004.06.001
Hwang, Heung Suk & Cho, Gyu Sung (2006). A Performance Evaluation Model for Order Picking Warehouse Design. Computers and Industrial Engineering, 51 (2), 335-342.
http://doi.org/10.1016/j.cie.2005.10.002
Javelin Group (2011). How Many Stores Will We Really Need? UK Non-Food Retailing in 2020. Disponible en: http://www.javelingroup. com/white_paper/white_paper_registration_how_many_stores/
Koo, Pyung-Hoi (2009). The Use of Bucket Brigades in Zone Order Picking Systems. OR Spectrum, 31 (4), 759-774. http://doi.org/10.1007/s00291-008-0131-x
Koster, René de (1994). Performance Approximation of Pick-To-Belt Order Picking Systems. European Journal of Operational Research, 72 (3), 558-573. http://doi.org/10.1016/0377-2217(94)90423-5. Disponible en: https://repub.eur.nl/pub/11836/PerformanceApproximation_1994pdf.pdf
Koster, René de; Le-Duc, Tho & Roodbergen, Kees Jan (2007). Design and Control of Warehouse Order Picking: A Literature Review. European Journal of Operational Research, 182 (2), 481-501. http://doi.
org/10.1016/j.ejor.2006.07.009. Disponible en: http://roodbergen.com/publications/EJOR2007.pdf
Le-Duc, Tho & Koster, René de (2007). Travel Time Estimation and Order Batching in a 2-Block Warehouse. European Journal of Operational Research, 176 (1), 374-388.
http://doi.org/10.1016/j.ejor.2005.03.052
Liao, Shu-hsien; Chen, Yin-ju & Lin, Yi-tsun (2011). Mining Customer Knowledge to Implement Online Shopping and Home Delivery for Hypermarkets. Expert Systems with Applications, 38 (4), 3982-3991.
http://doi.org/10.1016/j.eswa.2010.09.059. Disponible en: ftp://140.131.110.38/leecc/public/SPSS&AppofStatistics/2011Papers/Reference/Mining%20customer%20knowledge%20to%20implement%20online%20shopping%20and%20home%20delivery%20for%20hypermarkets.pdf
Martello, Silvano & Toth, Paolo (1987). Algorithms for Knapsack Problems. North- Holland Mathematics Studies, 132 (C), 213-257. http://doi.org/10.1016/S0304-0208(08)73237-7
Pan, Jason Chao-Hsien; Shih, Po-Hsun & Wu, Ming-Hung (2015). Order Batching in a Pick-and-Pass Warehousing System with Group Genetic Algorithm. Omega, 57, 238-248. http://doi.org/10.1016/j.
omega.2015.05.004
Park, Minyoung & Regan, Amelia (2004). Issues in Emerging Home Delivery Operations. University of California Transportation Center, 2 (2), 1-13. http://doi.org/10.1068/a201285
Rincón-García, Nicolás (2016). Freight Transport, Routing Software and Time- Dependent Vehicle Routing Models. Doctoral Thesis. University of Southampton, Faculty of Engineering and the Environment, Southampton, England. Disponible en: https://eprints.soton.ac.uk/397141/1/FINAL%2520ETHESIS%2520FOR%2520EPRINTS%252025739344.pdf
Saskia, Seidel; Mareï, Nora & Blanquart, Corinne (2016). Innovations in e-Grocery and Logistics olutions for Cities. Transportation Research Procedia, 12, 825-835. http://doi.org/10.1016/j.trpro.2016.02.035
Visser, Johan; Nemoto, Toshinori & Browne, Michael (2014). Home Delivery and the Impacts on Urban Freight Transport: A Review. Procedia - Social and Behavioral Sciences, 125, 15-27. http://doi.org/10.1016/j.sbspro.2014.01.1452
Yu, Mengfei & Koster, René de (2010). Enhancing Performance in Order Picking Processes by Dynamic Storage Systems. International Journal of Production Research, 48 (16), 4785-4806. http://doi.
org/10.1080/00207540903055693
Como Citar
Otero-Caicedo, R., Bolívar, S., & Rincón-García, N. (2017). Comparação através do picking em loja de duas alternativas de entrega em um ambiente de entrega em domicílios em supermercados. Área temática: logística na cidade. Cuadernos De Contabilidad, 17(44). https://doi.org/10.11144/Javeriana.cc17-44.ctpt
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