Slot Machine RTP Optimization Using Variable Neighborhood Search

Pantelis-Arsenios Kamanas, Angelo Sifaleras and Nikolaos Samaras

Mathematical Problems in Engineering, 2021, vol. 2021, 1-8

Abstract:

This work presents a Variable Neighborhood Search (VNS) approach for solving the Return-To-Player (RTP) optimization problem. A large number of software companies in the gaming industry seek to solve the RTP optimization problem in order to develop modern virtual casino gambling machines. These slot machines have a number of reels (e.g., three or more) that spin once a button is pushed. Each slot machine is required to have an RTP in a particular range according to the legislation of each country. By using a VNS framework that guides two local search operators, we show how to control the distribution of the symbols in the reels in order to achieve the desired RTP. In this study, optimization refers only to base game, the core of slot machine games, and not in bonus games, since a bonus game is triggered once two, three, or more specific symbols occur in the gaming monitor. Although other researchers have tried to solve the RTP problem in the past, this is the first time that a VNS methodology is proposed for this problem in the literature with good computational results.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8784065

DOI: 10.1155/2021/8784065

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