Integrated planning for product selection, shelf-space allocation, and replenishment decision with elasticity and positioning effects

Kim, Gwang; Moon, Ilkyeong

doi:10.1016/j.jretconser.2020.102274

Cited by 20 publications

(8 citation statements)

References 43 publications

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“…They considered space and cross-space elasticities and positioning effects on each product demand. They proposed tabu search and genetic algorithms to solve the problem [ 2 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Obviously, in today’s industrial world, given the increasing diversity of inventory control characteristics, inventory assortment planning seems necessary [ 2 ]. Traditional indicators are not able to meet all the needs of the organization’s inventory control system, and it is possible that new assortment planning indicators will be used with the help of the organization.…”

Section: Introductionmentioning

confidence: 99%

“…An important parameter that significantly affects the modeling of the assortment problem is substitution. When customers do not find their favorite product, they may substitute it with another similar product [ 1 , 2 ]. The willingness of customers to substitute a product with a similar one within its category is an important factor in AP; when there is the willingness to substitute a product, providing a great deal of inventory for that product is not so critical [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

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An integrated optimization model and metaheuristics for assortment planning, shelf space allocation, and inventory management of perishable products: A real application

Sajadi

Ahmadi

2022

PLoS ONE

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Product category management (PCM) plays a pivotal role in today’s large stores. PCM manages to answer questions such as assortment planning (AP) and shelf space allocation (SSA). AP problem seeks to determine a list of products and suppliers, while SSA problem tries to design the layout of the selected products in the available shelf space. These problems aim to maximize the retailer sales under different constraints, such as limited purchasing budget, limited space of classes for displaying the products, and having at least a certain number of suppliers. This paper makes an attempt to develop an integrated mathematical model to optimize integrated AP, SSA, and inventory control problem for the perishable products. The objective of the model is to maximize the sales and retail profit, considering the costs of supplier contracting/selecting and ordering, assortment planning, holding, and procurement cost. GAMS BARON solver is hired to solve the proposed model in small and medium scales. However, because the problem is NP-hard, an evolutionary genetic algorithm (GA), and an efficient local search vibration damping optimization (VDO) algorithm are proposed. A real case study is considered to evaluate the effectiveness and capabilities of the model. Besides, some test problems of different sizes are generated and solved by the proposed metaheuristic solvers to confirm the efficient performance of proposed algorithms in solving large-scale instances.

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“…They considered space and cross-space elasticities and positioning effects on each product demand. They proposed tabu search and genetic algorithms to solve the problem [ 2 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An integrated optimization model and metaheuristics for assortment planning, shelf space allocation, and inventory management of perishable products: A real application

Sajadi

Ahmadi

2022

PLoS ONE

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“…The benefit arising from the assignment of a product category to a market shelf depends on the attractiveness of the shelf segments to which it is allocated and its overall size. Kim and Moon (2021) conducted research on product selection and replenishment considering twodimensional shelves and the factors of customer demand for products such as space and cross-space elasticities and positioning effects. Ghoniem, Flamand, and Haouari (2016), employed in their study estimated traffic densities which correspond to the relative attractiveness of shelf segments.…”

Section: Shelf Segmentsmentioning

confidence: 99%

Merchandising rules for shelf space allocation with product categorization and vertical positioning

Субботин¹,

Czerniachowska²

2021

Informatyka Ekonomiczna

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Visual merchandising is assumed to be the main component of retailing; the significance of it is highlighted by academics and practitioners. This research focused on the in-store merchandising strategy of product allocations and describes the relations between such tactics and customers' perception of store layout, traffic direction, brand awareness, and the appropriate assigning of products to shelf levels, based on their brand as well as price. For retailers, this study provides an overview of incorporating different merchandising tactics into a shelf space allocation model which is applicable at stores selling branded and popular * The project is financed by the Ministry of Science and Higher Education in Poland under the program "Regional Initiative of Excellence" 2019-2022, project number 015/RID/2018/19, total funding amount 10,721,040.00 PLN.fast-moving products. The authors carefully adapted the product allocation approach on the planogram, as well as the way in which products could be placed on different shelf levels. This model satisfies the retailers' goals and may have a significant effect on sales. Thus, the study provides essential insights into the influence of other products, such as complementary, substitutable and clustered ones, in the assortment range.

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“…The challenges of shelf layouts and patterns have caught the attention of market researchers. The authors of [15][16][17][18] found that factors that may significantly influence customers' purchasing decisions include shelf space allocation and layout display. Personal or social factors may also influence the urge to purchase another product, a phenomenon that has been studied via Market Basket Analysis [19][20][21][22][23][24][25], which analyzes the correlation of products that customers are most likely to buy at the same time [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Design of Profit Volumes and Closeness Ratings Using MBHS Optimizing Based on the PrefixSpan Mining Approach (PSMA) for Product Layout in Supermarkets

Kaewyotha

Songpan

2021

Applied Sciences

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Product layout significantly impacts consumer demand for purchases in supermarkets. Product shelf renovation is a crucial process that can increase supermarket efficiency. The development of a sequential pattern mining algorithm for investigating the correlation patterns of product layouts, solving the numerous problems of shelf design, and the development of an algorithm that considers in-store purchase and shelf profit data with the goal of improving supermarket efficiency, and consequently profitability, were the goals of this research. The authors of this research developed two types of algorithms to enhance efficiency and reach the goals. The first was a PrefixSpan algorithm, which was used to optimize sequential pattern mining, known as the PrefixSpan mining approach. The second was a new multi-objective design that considered the objective functions of profit volumes and closeness rating using the mutation-based harmony search (MBHS) optimization algorithm, which was used to evaluate the performance of the first algorithm based on the PrefixSpan algorithm. The experimental results demonstrated that the PrefixSpan algorithm can determine correlation rules more efficiently and accurately ascertain correlation rules better than any other algorithms used in the study. Additionally, the authors found that MBHS with a new multi-objective design can effectively find the product layout in supermarket solutions. Finally, the proposed product layout algorithm was found to lead to higher profit volumes and closeness ratings than traditional shelf layouts, as well as to be more efficient than other algorithms.

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Integrated planning for product selection, shelf-space allocation, and replenishment decision with elasticity and positioning effects

Cited by 20 publications

References 43 publications

An integrated optimization model and metaheuristics for assortment planning, shelf space allocation, and inventory management of perishable products: A real application

An integrated optimization model and metaheuristics for assortment planning, shelf space allocation, and inventory management of perishable products: A real application

Merchandising rules for shelf space allocation with product categorization and vertical positioning

Multi-Objective Design of Profit Volumes and Closeness Ratings Using MBHS Optimizing Based on the PrefixSpan Mining Approach (PSMA) for Product Layout in Supermarkets

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