Modified dynamic programming model with limited order picking capacity / Noraimi Azlin Mohd Nordin

Noraimi Azlin , Mohd Nordin (2021) Modified dynamic programming model with limited order picking capacity / Noraimi Azlin Mohd Nordin. PhD thesis, Universiti Malaya.

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Abstract

Order picking process in a warehouse is considered as a critical stage in managing customers’ service. It is a process of retrieving goods from specified storage locations according to picking lists, and formed order according to customers’ needs. Nowadays, orders can be made through typical style by going to the shop and via online. Since ordering process is fast, customers expect to have fast return in delivery of items. Organizations need to make sure their warehouse management system is able to provide fast and efficient service to meet the standard of customers, also to adapt this new situation. In most warehouses, the order picking process is pictured as the most costly and crucial, especially in retail networks and online shops since the order picking process consumes up to 70% of all warehouse labour activities. Not only that, the costs involved in managing such procedure also is a costly operation. Nowadays, warehouses may also suffering from a limited funds and budget cuts. In handling this scenario, the decisionmakers need to take any possible action to ensure the warehouses can keep operating and meeting the requirements and satisfaction of the customers. This include provide better service, quality items, maximum profit with minimum service level and some may affected to downsizing their operation in warehouses. Not only that, the motivation and welfare of the staffs need also to be considered in making sure the above requirements are fulfilled. However, any changes or action take could somehow limit the production level, hence, increase the response time and waiting time in the system. This means, demand may be increase but due to limited supply and availability of products will results to customers leaving the process or at certain level, leave the system. Thus, proper system and efficient management is pinnacle in making sure the target of management could always been achieved. Throughout the study, the system in the end is hoped to develop a proper procedures in order picking routine. This include different routing picking schemes that can significantly improve the order picking process results and reduce costs of the management related to order picking. Strategic locations of order pickers and picking items, systematic movement of these order pickers and minimum travel time taken to collect items are among the key factors that may reduce the waiting time of the customers. In achieving this, the objectives of the study are firstly, to develop layout routing network that is compatible with the layout of the warehouse. Next, to determine either Dijsktra’s algorithm or Dynamic Programming Method will give the most accurate shortest path and minimum travel time for order pickers. Thirdly is to develop mathematical order picking model for an automotive manufacturing company that meets the requirement of limited picking capacity and fixed number of pickers. Fourthly is to test and compare the developed mathematical order picking model with secondary data and finally to simulate the data into three types of categories; small, medium and large. The simulation was done to test whether the manufacturing company are able to cater for any variants number of demand made by customers using our mathematical model developed. The proposed model was adapted and used to solve real-case studies from the automotive manufacturing company in Malaysia. The results show a reduced of total distance by 11.6% by choosing the shortest path based on the number of order pickers and also an increased by 48% using batch picking method. Next, the dynamic simulation analysis based on the actual scenario of varying number of orders are performed. Here, the orders are categorised as small, medium and large order. The simulated results show that the picker travel time can be reduced by about 44.89%. Through this simulation model, it also helps to visualise the benefits that it may reduce the waiting time of customers that leads to increase in customers’ satisfaction. Concurrently, the motivation of workers is also considered. This study may also contribute to problem solving issues to any warehouse operation with similar procedure.

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