Slot machine RTP optimization using variable neighborhood search

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 seeks 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 which 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 manuscript, 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.