Any global provider of logistics solutions has to deal with the pressing task of dealing with a multitude of order lines or picking cartons per day. The warehouse is involved in the task of carton picking and it ranges in the order of thousands when the company in concern is a leading global logistics provider. Therefore, it is essential to develop a suitable algorithm that can be employed in the task of multi-order picking. The workforce of the warehouse is dedicated to completing the picking-of-order operations which involve picking up goods and arranging them in cartons in an orderly fashion.
Problems and challenges that the global logistics provider will face while implementing this simulation algorithm :
The accurate numbers had been provided which would act as the data involved in the order picking problems. The trolleys or fangos have a minimum and maximum capacity of carrying cartons, out of which, few are positioned on the weighing scales of the trolleys. The weighing scales are utilized in enhancing the picking accuracy by issuing a statutory alarm signal which is generated when the weight of the picked goods is different from that of the master data.
An operator is engaged with the task of filling in the cartons which are positioned on the scales of the trolleys and when one carton is loaded with products or items, it is swapped with the next empty carton in which the filling procedure is performed. Therefore, only the maximum number of cartons that the trolleys can carry at any given point of time is always available for simultaneous filling. The articles or the items of the cartons can be positioned at any location which is present along the operator’s route. Thus, it springs the need for an algorithm for establishing optimal picking tours to serve incoming orders.
Solutions to the multi-order picking process :
The required algorithm that can do away with all the complexities and complications resulting from the glitches in the executions of multi-order picking, is needed to be developed. The best company or organization should be provided with the case study data and employed with the task of developing this intuitive algorithm. The algorithm would consist of an idea that operates on the fundamental that the operator’s route is always straight so that the operator does not need to go back after swapping cartons. Therefore a maximum number of cartons cannot be assigned to a single order-picking tour and instead cartons may contain items from the initial as well as final locations of the tour and should not be swapped until full.
The experts engaged with the task of developing the appropriate algorithm should run or test the algorithm on a simulation model of the warehouse to test its efficiency before employing it in real-time functions of the warehouse. The detailed simulation model should highlight the entire layout of the warehouse including the places of storage, movement of trolley operators, inbound orders, trolley operations as well as service levels.
The optimization of the routes followed by the operators can be modified depending on a couple of criteria :
- Maximizing average cartons quantity per tour
- Maximizing article overlap in each tour which highlights the preference of selecting the same articles for multiple cartons in a single tour.
The output data which would result from the algorithm after feeding this input data would contain the number of cartons which can be successfully filled per tour, the average utilization of a trolley as well as the determination of the meantime of a tour.
Results of implementing the perfect algorithm :
The output statistics generated from the algorithm after implementing it to the simulation models of the warehouse, explicitly display the improvement of trolley utilization rate by almost 150% as compared to the former trolley utilization rate. Of course, this included the suggested inclusion of the remodeling of layout configuration, equipment, and movement algorithm. This model can thus be imposed with the task of choosing the perfect warehouse layout and improved design for article distribution in the warehouse. The trolley utilization rate and the trolley numbers would also define a balance between the staff workloads and the service levels.
Thus it is extremely essential in the wake of the modern and mechanized warehouses to develop a sustaining algorithm that can develop the optimization in procedures like service level, trolley utilization, and workforce efficiency. This would also result in the modification of the warehousing design according to the data generated from the implementation of the algorithm.