scholarly journals Slot Machine RTP Optimization Using Variable Neighborhood Search

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Pantelis-Arsenios Kamanas ◽  
Angelo Sifaleras ◽  
Nikolaos Samaras
Keyword(s):  
Optimization Problem ◽  
Variable Neighborhood Search ◽  
Slot Machine ◽  
Casino Gambling ◽  
Slot Machines ◽  
Neighborhood Search ◽  
Gaming Industry ◽  
Software Companies ◽  
Machine Games ◽  
First Time

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.

scholarly journals The maximum rewards at the minimum price: Reinforcement rates and payback percentages in multi-line slot machines

2011 ◽  
pp. 11 ◽  
Author(s):  
Kevin Harrigan ◽  
Michael Dixon ◽  
Vance MacLaren ◽  
Karen Collins ◽  
Jonathan Fugelsang
Keyword(s):  
Detailed Analysis ◽  
Past Research ◽  
Reinforcement Rate ◽  
Slot Machine ◽  
Slot Machines ◽  
Losses Disguised As Wins ◽  
Minimum Price ◽  
Machine Games ◽  
Payback Percentage

Past research has shown that gamblers frequently use the mini-max strategy in multi-line slot machines, whereby the player places the minimum bet on the maximum number of lines. Through a detailed analysis and explanation of the design of multi-line slot machine games, we show that when using the mini-max strategy, the payback percentage remains unchanged, yet the reinforcement rate is significantly increased. This increase in reinforcement rate is mainly due to spins in which the amount won is less than the amount wagered, which we call losses disguised as wins. We have verified these conclusions by playing an actual slot machine game for 10,000 spins and recording the results. We believe that the high reinforcement rate that results from playing multiple lines on games of this type contributes to their potential addictiveness. We provide three theories for why players use the mini-max strategy and suggest further areas of research.

scholarly journals AGV Scheduling Optimization for Medical Waste Sorting System

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xueting He ◽  
Hao Quan ◽  
Wanlong Lin ◽  
Weiliang Deng ◽  
Zheyi Tan
Keyword(s):  
Optimization Problem ◽  
Variable Neighborhood Search ◽  
Programming Model ◽  
Dynamic Programming Algorithm ◽  
Medical Waste ◽  
Mixed Integer ◽  
Programming Algorithm ◽  
Neighborhood Search ◽  
Operational Flow ◽  
Sorting System

The dramatic increase in medical waste has put a severe strain on sorting operations. Traditional manual order picking is extremely susceptible to infection spread among workers and picking errors, while automated medical waste sorting systems can handle large volumes of medical waste efficiently and reliably. This paper investigates the optimization problem in the automated medical waste sorting system by considering the operational flow of medical waste. For this purpose, a mixed-integer programming model is developed to optimize the assignment among medical waste, presorting stations, and AGVs. An effective variable neighborhood search based on dynamic programming algorithm is proposed, and extensive numerical experiments are conducted. It is found that the proposed algorithm can efficiently solve the optimization problem, and the sensitivity analysis gives recommendations for the speed setting of the conveyor.

scholarly journals VARIABLE NEIGHBORHOOD SEARCH FOR ORDER BATCHING IN A WAREHOUSE

2009 ◽  
Vol 26 (05) ◽  
pp. 655-683 ◽  
Author(s):  
MARIA ALBAREDA-SAMBOLA ◽  
ANTONIO ALONSO-AYUSO ◽  
ELISENDA MOLINA ◽  
CLARA SIMÓN DE BLAS
Keyword(s):  
Comparative Analysis ◽  
Travel Time ◽  
Optimization Problem ◽  
Variable Neighborhood Search ◽  
Solution Space ◽  
Neighborhood Search ◽  
Heuristic Methods ◽  
Order Batching ◽  
Policy Routing ◽  
Total Travel Time

In this paper we address the problem of batching orders in a warehouse, with the objective of minimizing the total travel time. Order batching is an NP-hard optimization problem that is very difficult to solve exactly in practice. Thus, most implemented solutions are based on elementary heuristic methods that perform a relatively limited exploration of the solution space. As an alternative, we propose a heuristic based on variable neighborhood search, where the emphasis is placed on performing an intensive exploration of the most promising regions of the solution space. Simulations are conducted to study the performance of the method with different warehouse configurations, and an exhaustive comparative analysis, which considers all the best known heuristics, is carried out. The results obtained show that the proposed heuristic is competitive and that it provides a suitable method which can be used in practice. Additionally, since the performance of the algorithms depends heavily on factors such as storage policy, routing strategies, or the structure of the orders, we have developed an ANOVA in order to consider the effect of all the above factors on the different methods tested.

scholarly journals PAR Sheets, probabilities, and slot machine play: Implications for problem and non-problem gambling

2009 ◽  
pp. 81 ◽  
Author(s):  
Kevin A. Harrigan ◽  
Mike Dixon
Keyword(s):  
Problem Gambling ◽  
Structural Characteristics ◽  
Slot Machine ◽  
Slot Machines ◽  
Freedom Of Information ◽  
Reinforcement Schedules ◽  
Near Misses ◽  
Privacy Act ◽  
Design Documents ◽  
Machine Games

Through the Freedom of Information and Protection of Privacy Act, we obtained design documents, called PAR Sheets, for slot machine games that are in use in Ontario, Canada. From our analysis of these PAR Sheets and observations from playing and watching others play these games, we report on the design of the structural characteristics of Ontario slots and their implications for problem gambling. We discuss characteristics such as speed of play, stop buttons, bonus modes, hand-pays, nudges, near misses, how some wins are in fact losses, and how two identical looking slot machines can have very different payback percentages. We then discuss how these characteristics can lead to multi-level reinforcement schedules (different reinforcement schedules for frequent and infrequent gamblers playing the same game) and how they may provide an illusion of control and contribute in other ways to irrational thinking, all of which are known risk factors for problem gambling.

scholarly journals A Variable Neighborhood Search Algorithm for the Leather Nesting Problem

2012 ◽  
Vol 2012 ◽  
pp. 1-28
Author(s):  
Cláudio Alves ◽  
Pedro Brás ◽  
José M. Valério de Carvalho ◽  
Telmo Pinto
Keyword(s):  
Automotive Industry ◽  
Optimization Problem ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Cutting And Packing ◽  
Car Seats ◽  
Nesting Problem ◽  
Neighborhood Search Algorithm ◽  
Additional Constraints

The leather nesting problem is a cutting and packing optimization problem that consists in finding the best layout for a set of irregular pieces within a natural leather hide with an irregular surface and contour. In this paper, we address a real application of this problem related to the production of car seats in the automotive industry. The high quality requirements imposed on these products combined with the heterogeneity of the leather hides make the problem very complex to solve in practice. Very few results are reported in the literature for the leather nesting problem. Furthermore, the majority of the approaches impose some additional constraints to the layouts related to the particular application that is considered. In this paper, we describe a variable neighborhood search algorithm for the general leather nesting problem. To evaluate the performance of our approaches, we conducted an extensive set of computational experiments on real instances. The results of these experiments are reported at the end of the paper.

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