Artificial Intelligence Applied to Assigned Merchandise Location in Retail Sales Systems

Abstract

This paper presents an option for improving the process of assigning storage locations for merchandise in a warehouse. A disadvantage of policies in the literature is that the merchandise is assigned allocation only according to the volume of sales and the rotation it presents. However, in some cases it is necessary to deal with other aspects such as family group membership, the physical characteristics of the products, and their sales pattern to design an integral policy. This paper presents an alternative to the aforementioned process using Flexsim ® , artificial neural networks, and genetic algorithms. OPSOMMING'n Metode om die toekenningsproses van stoorplekke vir goedere in 'n pakhuis te verbeter, word voorgehou. 'n Nadeel van die bestaande beleide in die literatuur is dat die goedere slegs toegeken word op grond van die verkoopvolume en die omset wat dit verteenwoordig. In sommige gevalle is dit egter nodig om ander aspekte, soos familie groeplidmaatskap, die fisiese eienskappe van die produkte en hulle verkoopspatroon, te oorweeg om 'n integrale beleid te formuleer. Hierdie artikel beskryf 'n alternatief vir die voorafgenoemde proses deur van Flexsim ® , kunsmatige neurale netwerke en genetiese algoritmes gerbuik te maak.

Establishing a Novel Algorithm for Highly Responsive Storage Space Allocation Based on NAR and Improved NSGA‐III

“…For example, Li et al [8] defined a new dynamic storage space allocation problem based on ABC classification and association between products, using genetic algorithms to deal with computational complexity and developing an integrated mechanism for optimization. Cruz-Dominguez and Santos-Mayorga [25] used a combination of genetic algorithms and artificial neural networks to minimize the order preparation for a given input condition considering the physical characteristics of the products and their sales patterns. Kim and Smith [26] used an improved simulated annealing algorithm to derive the algorithm's effectiveness to solve the space allocation problem based on data arithmetic examples of large distribution systems.…”

An Artificial Intelligence and Knowledge-Based System to Support the Decision- Making Process in Sales

“…Knowledge-based intelligent systems contribute to an improved business decision-making process, since managers have difficulty organising all available data manually, as becomes evident when they are needed for decision-making [5,6]. Intelligent systems have the ability efficiently to store and retrieve large amounts of data that will be needed to solve problems or make decisions [27]. Due to their autonomous and rational abilities, in addition to streamlining the company's workflow, intelligent systems also ensure the automation and standardisation of business processes, thus optimising them [7].…”

Optimisation of Stock Keeping Unit Placement in a Retail Distribution Centre

“…Various slotting criteria have been derived from generally accepted best practices [4,5]. These criteria are considered by inventory managers during slotting decisions.…”