scholarly journals A STUDY OF THE EFFECT OF THE PARAMETERS FOR OPTIMIZING PROFIT USING SIMULATED ANNEALING TO SOLVE SHELF SPACE ALLOCATION PROBLEM

2020 ◽  
Vol 3 (2) ◽  
pp. 255-268
Author(s):  
Romit S. Beed ◽  
◽  
Ankita Sarkar ◽  
Raya Sinha ◽  
Deboshruti Dasgupta
Keyword(s):  
Simulated Annealing ◽  
Optimization Problems ◽  
Programming Model ◽  
Limited Resource ◽  
Allocation Problem ◽  
Shelf Space ◽  
Combinatorial Optimization Problems ◽  
Space Allocation ◽  
Conflicting Objectives ◽  
Shelf Space Allocation

Shelf space allocation has always remained a crucial issue for any retail store, as space is a limited resource. This work proposes a model that uses a hyper-heuristic approach to allocate products on shelves to maximize the retailer's profit. This work has concentrated on providing a solution specifically for a consumer packaged goods store. There exist multiple conflicting objectives and constraints which influence the profit. The consequence is a non-linear programming model having a complex objective function, which is solved by using multiple neighborhood approaches using simulated annealing as simulated annealing is a useful tool for solving complex combinatorial optimization problems. Detailed analysis of the proposed technique of using annealing and reheating has revealed the effectiveness in profit maximization in the shelf space allocation problem. Various simulated annealing parameters have been studied in this paper, which provides optimum values for maximizing profit.

A DYNAMIC PROGRAMMING HEURISTIC FOR RETAIL SHELF SPACE ALLOCATION PROBLEM

2011 ◽  
Vol 28 (02) ◽  
pp. 183-199 ◽  
Author(s):  
HASMUKH K. GAJJAR ◽  
GAJENDRA K. ADIL
Keyword(s):  
Dynamic Programming ◽  
Optimal Solution ◽  
Retail Store ◽  
Allocation Problem ◽  
Shelf Space ◽  
Reasonable Time ◽  
Cpu Time ◽  
Local Search Heuristic ◽  
Space Allocation ◽  
Shelf Space Allocation

Shelf space allocation to products greatly impacts the profitability in a retail store. In this paper, we consider a retail shelf-space allocation problem where retailer wishes to allocate the available spaces of different shelves to a large number of products considering direct space elasticity in the product's demand. There is a great interest to develop efficient heuristics due to NP-hard nature of this problem. We propose a dynamic programming heuristic (DPH) to obtain near optimal solution in a reasonable time to solve this problem. The empirical results found that DPH obtained near optimal solutions for randomly generated instances of problems with size (products, shelves) varying from (100, 30) to (200, 50) within a few seconds of CPU time. The performance of DPH is benchmarked against an existing local search heuristic (LSH). It was found that DPH takes substantially less CPU time and attains a solution close to that obtained by LSH. Thus, DPH has great potential to solve the problem of realistic size within reasonable time. The proposed DPH is also applied to a case of an existing retail store.

scholarly journals Simulated Annealing Hyper-Heuristic for a Shelf Space Allocation on Symmetrical Planograms Problem

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1182
Author(s):  
Kateryna Czerniachowska ◽  
Marcin Hernes
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Profit Maximization ◽  
Point Of View ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Effective Decision Making ◽  
Shelf Space Allocation

The allocation of products on shelves is an important issue from the point of view of effective decision making by retailers. In this paper, we investigate a practical shelf space allocation model which takes into account the number of facings, capping, and nesting of a product. We divide the shelf into the segments of variable size in which the products of the specific types could be placed. The interconnections between products are modelled with the help of categorizing the products into specific types as well as grouping some of them into clusters. This results in four groups of constraints—shelf constraints, shelf type constraints, product constraints, position allocation constraints—that are used in the model for aesthetic symmetry of a planogram. We propose a simulated annealing algorithm with improvement and reallocation procedures to solve the planogram profit maximization problem. Experiments are based on artificial data sets that have been generated according to real-world conditions. The efficiency of the designed algorithm has been estimated using the CPLEX solver. The computational tests demonstrate that the proposed algorithm gives valuable results in an acceptable time.

Swarm Intelligence Approaches to Shelf Space Allocation Problem with Linear Profit Function

2016 ◽  
pp. 22-41
Author(s):  
Tuncay Ozcan ◽  
Şakir Esnaf
Keyword(s):  
Swarm Intelligence ◽  
Allocation Problem ◽  
Profit Function ◽  
Allocation Decision ◽  
Shelf Space ◽  
Space Management ◽  
Bee Colony ◽  
Space Allocation ◽  
Problem Instances ◽  
Shelf Space Allocation

The efficient management of shelf space carries critical importance on both the reduction of operational costs and improvement of financial performance. In this context, which products to display among the available products (assortment decision), how much shelf space to allocate the displayed products (allocation decision) and which shelves to display of each product (location decision) can be defined as main problems of shelf space management. In this paper, allocation problem of shelf space management is examined. To this end, a model which includes linear profit function is used for the shelf space allocation decision. Then, heuristic approaches are developed based on particle swarm optimization and artificial bee colony for this model. Finally, the performance analysis of these approaches is realized with problem instances including different number of products and shelves. Experimental results show that the proposed swarm intelligence approaches are superior to Yang's heuristics for the shelf space allocation model.

A Multiobjective Evolutionary Algorithm for the Linear Shelf Space Allocation Problem

2008 ◽  
pp. 1001-1010
Author(s):  
Anna I. Esparcia-Alcázar ◽  
Ana I. Martínez-García ◽  
Jose M. Albarracín-Guillem ◽  
Marta E. Palmer-Gato ◽  
Juan J. Merelo ◽  
...  
Keyword(s):  
Evolutionary Algorithm ◽  
Allocation Problem ◽  
Shelf Space ◽  
Multiobjective Evolutionary Algorithm ◽  
Space Allocation ◽  
Shelf Space Allocation

scholarly journals A Heuristic Approach for Shelf Space Allocation Problem

2015 ◽  
Vol 4 (1) ◽  
pp. 38
Author(s):  
A. Hande Erol Binguler ◽  
Serol Bulkan ◽  
Mustafa Agaoğlu
Keyword(s):  
Heuristic Approach ◽  
Allocation Problem ◽  
Shelf Space ◽  
Space Allocation ◽  
Shelf Space Allocation
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