Warehouse Process Optimization

The research given in this study implicates the problems at the observed warehouse from which certain data were collected. The methodology of research consists of data collected from WMS and data collected chromatographically at the location. Also, various authors suggest different answers to related similar problems regarding warehouse process optimization. Cold supply chains have high levels of greenhouse gas emissions due to high energy consumption and refrigerant gas leaks and for this problem, the solution consists of dealing with managing inventory by using a known
policy but without explicit formulas for the inventory cost and maximum level functions. Precisely, a novel hybrid simulation-optimization approach is proposed for problem-solving. Lagrangian decomposition is used to compose the model into an integer programming sub-problem and sets of single variable concave minimization subproblems that are solved using the simulating approach. The formula given by the named authors combines the efficiency of optimization methods with the accuracy of simulation methods. By using it, not only is the process optimization reached, but the
warehouse processes are also turning green and sustainable. Author Lu [7] conducted research for an algorithm for dynamic order-picking in warehouses, and according to it, the dynamic order-picking strategies that allow changes of pick-lists during a picked cycle are of importance. In this paper, authors gave the routing algorithm for optimizing the dynamic order picking routes for a manual picker to part system, which is also used in the warehouse described in the main research of this study. Their guidelines can provide a warehouse design close to the optimal solution; precisely, they limit the decision variables and include size and layout of the shipping area, dock door configuration, pallet shape and pallet rack height. For developing the design guidelines, they employ a statistical-based methodology, where one set of data is used to develop the guidelines and an independent set of data is used to evaluate the performance of the guidelines. The response variable is the number
of labour hours which is evaluated for each design in the solution space, but the most impactful parameter is using a forward area. Refer to warehouse reshuffling as a reorganization strategy and claim that it can be optimized using a mathematical programming formulation, based on heuristics. The given results suggest that the proposed heuristics improves upon a benchmarking heuristics by relaxing how cycles are handled and incorporating double-handling. It is necessary to emphasize the problem given in this, and also include double-handling. The warehouse layout decision is important as it affects several aspects of a warehouse, including various costs and storage capacity. A step  toward warehouse optimization is by use of their algorithm that determines lane depth, number of storage levels, lateral depth and longitudinal width of a three-dimensional order picking warehouse. It also helps in knowing the quantum of change in the cost due to change in different parameters, which is difficult to predict due to the interaction of multiple effects and trade-offs. also base their research on Lagrangian relaxation, precisely on a heuristic algorithm based on Lagrangian relaxation and sub-gradient optimization methods. The use of this algorithm is planned for minimizing the sum of warehouse operation costs, inventory costs and transportation costs. In the conducted study, the use of the developed algorithm, compared with the full-turnover storage,reduces maximal 2.08% of the average travel distance per picking. Authors Lu et al. [7] developed an interventionist routing algorithm for optimizing dynamic order picking. The algorithm re-calculates the optimal route during the picking operation and is tested using a set of stimulations based on an industrial case. The results given in this study indicate that, under a range of conditions, the algorithm can outperform both static and heuristic dynamic order picking routing algorithms. The conducted research in the form of a case study will implicate how certain organizational changes may contribute to reducing the process time and influence higher quality processing. Based on warehouse processes of dairy industry on the Croatian market, the paper will suggest process optimization. On-site data collection, continuous process management and control can optimize the observed warehouse process, with the limitation of optimal process life cycle duration, regarding the possibility of upgrading in a certain upcoming period