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Content available remote Shelf space allocation models in retail enterprise
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EN
Shelf space is a limited and very expensive resource as a lot of products are presented in a retail store. Shelf space is used in retail enterprise for multiple purposes e.g. allocation of products, ensuring brand visibility, improving customers satisfaction etc. This paper proposed two new practical shelf space allocation models which may be used in retail enterprise helping the retailer to increase gained profit. Both models enrich basic shelf space allocation problem with complicated merchandising rules such as allocation of product on different vertical levels according their price subcategories (1st model) and allocation of products in different shelf segments based on the products types, brand, weight, and package (2nd model).
EN
Major manufactures are moving towards a sustainability goal. This paper introduces the results of collaboration with the leading company in the packaging and advertising industry in Germany and Poland. The problem addresses the manufacturing planning problem in terms of minimizing the total cost of production. The challenge was to bring a new production planning method into cardboard manufacturing and paper processing which minimizes waste, improves the return of expenses, and automates daily processes heavily dependent on the production planners’ experience. The authors developed a module that minimizes the total cost, which reduces the overproduction and is used by the company’s manufacturing planning team. The proposed approach incorporates planning allowances rules to compromise the manufacturing requirements and production cost minimization.
EN
Distribution centres are the important elements of modern supply chains. A distribution centre stores and ships products. In this paper, we investigate the model of the dimensioning of shelf space on the rack with vertical and horizontal product categorisation in a distribution centre, where the objective is to maximise the total product movement/profit from all shelves of the rack which is being managed by a packer who needs to complete orders selecting the products from the shelves and picking them to the container. We apply two newly developed heuristics to this problem and compare the results to the optimal solution found by the CPLEX solver. There are 8 steering parameters that allow for reducing the search space implemented in heuristics. Among them are parameters that decrease the number of prod- ucts on the shelves, the category width range for assigning most space for the most profitable products within the category, two versions of steering parameters for the number of generated product allocations, the step parameters for the intensity of solution diversification, and the movement/profit below which the solutions are not generated. The computational results are presented and indicate that higher-quality solutions can be obtained using the new heuristics. In 10 from 15 tests, both heuristics can find optimal solutions without exploring the whole solution space. For the rest test sets, the solutions received by heuristics are not less than 92.58%.
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