Applied Stochastic Models in Business and Industry最新文献

{"title":"An initial investigation for employing ACH depth function in degradation model selection: A case study with real data","authors":"Arefe Asadi,&nbsp;Mitra Fouladirad,&nbsp;Diego Tomassi","doi":"10.1002/asmb.2844","DOIUrl":"10.1002/asmb.2844","url":null,"abstract":"<p>In degradation modeling, stochastic processes often do not meet the classical properties necessary for traditional goodness-of-fit tests. This paper presents an initial investigation into employing the ACH depth function and its potential in degradation model selection. We commence by presenting various stochastic processes as degradation models and their selection criteria. Subsequently, we delve into the ACH depth function, highlighting its potential in this context. Through simulated data, we assess the application of this functional depth measure for model selection. The methodology's validity is further reinforced by its application to real-world data, underscoring its effectiveness.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 3","pages":"598-619"},"PeriodicalIF":1.4,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139475668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal maintenance policy for imperfect production systems using reliability function and defect rate","authors":"Jyh-Wen Ho,&nbsp;Yeu-Shiang Huang,&nbsp;Peng-Tsi Huang","doi":"10.1002/asmb.2843","DOIUrl":"10.1002/asmb.2843","url":null,"abstract":"<p>This study examines how a manufacturer can improve the robustness of an imperfect production system by implementing maintenance activities, which can be measured in terms of system reliability and product failure rate. A two-dimensional maintenance policy comprising system reliability and the product defect rate is proposed to assess maintenance activity costs. The optimal thresholds of the two dimensions are analyzed to investigate the trade-off between cost and system quality. A numerical example is provided to verify the proposed model's effectiveness. The results showed that the less stable the system, the greater the total costs incurred; therefore, lower stringent thresholds may be set to prevent frequent maintenance. Moreover, a sensitivity analysis is performed to investigate the essential parameters that significantly affect maintenance decisions. The results showed that the thresholds of the reliability function and defect rate significantly impact total costs. Any inaccurate assessment of system usage could lead to incorrect estimations and a substantial increase in cost.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 3","pages":"813-825"},"PeriodicalIF":1.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139386884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demand for live betting: An analysis using state-space models","authors":"Marius Ötting,&nbsp;Rouven Michels,&nbsp;Roland Langrock,&nbsp;Christian Deutscher","doi":"10.1002/asmb.2836","DOIUrl":"10.1002/asmb.2836","url":null,"abstract":"<p>Sports betting markets have grown very rapidly recently, with the total European gambling market worth 98.6 billion euro in 2019. Considering a high-resolution (1 Hz) data set provided by a large European bookmaker, we investigate the demand for bet placements during matches and in particular the effect of news. Accounting for the general market activity level within a state-space modelling framework, we analyse the market's response to events such as goals (i.e., major news). Our results indicate that markets strongly react to news, but other factors, such as the day of the week and the uncertainty of outcome, also affect the stakes placed. We thus provide insights into the behaviour of bettors during matches, which can be relevant for bookmakers, for example to predict future revenues, but also for more specialised tasks such as fraud detection.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 2","pages":"527-541"},"PeriodicalIF":1.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2836","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139385595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian analysis of Markov modulated queues with abandonment","authors":"Atilla Ay,&nbsp;Joshua Landon,&nbsp;Süleyman Özekici,&nbsp;Refik Soyer","doi":"10.1002/asmb.2839","DOIUrl":"10.1002/asmb.2839","url":null,"abstract":"<p>We consider a Markovian queueing model with abandonment where customer arrival, service and abandonment processes are all modulated by an external environmental process. The environmental process depicts all factors that affect the exponential arrival, service, and abandonment rates. Moreover, the environmental process is a hidden Markov process whose true state is not observable. Instead, our observations consist only of customer arrival, service, and departure times during some period of time. The main objective is to conduct Bayesian analysis in order to infer the parameters of the stochastic system, as well as some important queueing performance measures. This also includes the unknown dimension of the environmental process. We illustrate the implementation of our model and the Bayesian approach by using simulated and actual data on call centers.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 3","pages":"791-812"},"PeriodicalIF":1.4,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139398011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dam management problem with energy production as an optimal switching problem","authors":"Etienne Chevalier,&nbsp;Cristina Di Girolami,&nbsp;M'hamed Gaïgi,&nbsp;Elisa Giovannini,&nbsp;Simone Scotti","doi":"10.1002/asmb.2840","DOIUrl":"10.1002/asmb.2840","url":null,"abstract":"<p>We consider an optimal stochastic control problem for a dam. Electrical power production is operating under an uncertain setting for electricity market prices and water level which has to be kept under control. Indeed, the water level inside the basin cannot exceed a certain threshold for safety reasons, and at the same time cannot decrease below another threshold in order to keep power production active. We model this situation as a mixed control problem with regular and switching controls under constraints. We characterize the value function as solution of an HJB equation and provide some numerical approximating methods. We shall illustrate by numerical examples the main achievements of the present approach.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 6","pages":"1596-1611"},"PeriodicalIF":1.3,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2840","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139062442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to deep reinforcement learning-based ordering mechanism for performance optimization in multi-echelon supply chains","authors":"Dony S. Kurian,&nbsp;V. Madhusudanan Pillai","doi":"10.1002/asmb.2838","DOIUrl":"10.1002/asmb.2838","url":null,"abstract":"<p>This paper addresses and acknowledges the valuable feedback provided by Dr. Deniz Preil in response to the recent study conducted by Kurian et al which investigates the application of proximal policy optimization (PPO) to determine dynamic ordering policies within multi-echelon supply chains. The first comment raised by Dr. Preil motivated an examination of the training and evaluation procedures in Experiments 2, 3, and 4. The Experiments 2 and 3 were reworked to address this, allowing the seed to vary for every training iteration, resulting in refined outcomes while there was no need of reworking of Experiment 4. The second comment focused on the benchmarking strategies involving the 1-1 policy and the order-up-to (OUT) policy, clarifying the distinctions between the two policies and justifying the use of the 1-1 policy for benchmarking in Experiment 4. The implementation of the widely accepted OUT policy was explained, highlighting the meaningful rationale behind its use. These discussions aim to enhance the methodology employed by Kurian et al and strengthen the implications of the findings within the domain of supply chain ordering management.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 5","pages":"1455-1465"},"PeriodicalIF":1.3,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139062161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic and statistical methods in commodity risk management","authors":"Fabio Antonelli,&nbsp;Roy Cerqueti,&nbsp;Alessandro Ramponi,&nbsp;Sergio Scarlatti","doi":"10.1002/asmb.2841","DOIUrl":"10.1002/asmb.2841","url":null,"abstract":"","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 2","pages":"220-223"},"PeriodicalIF":1.4,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139149631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bayesian change point prediction for downhole drilling pressures with hidden Markov models","authors":"Ochuko Erivwo,&nbsp;Viliam Makis,&nbsp;Roy Kwon","doi":"10.1002/asmb.2835","DOIUrl":"10.1002/asmb.2835","url":null,"abstract":"&lt;p&gt;In the drilling of oil wells, the need to accurately detect downhole formation pressure transitions has long been established as critical for safety and economics. In this article, we examine the application of Hidden Markov Models (HMMs) to oilwell drilling processes with a focus on the real time evolution of downhole formation pressures in its partially observed state. The downhole drilling pressure system can be viewed as a nonlinear, non-degrading stochastic process whose optimum performance is in a region in its warning state prior to random failure in time. The differential pressure system &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;∆&lt;/mo&gt;\u0000 &lt;mi&gt;P&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ left(Delta Pright) $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; is modeled as a hidden 3 state continuous time Markov process. States 0 and 1 are not observable and represent the normally pressured (initiating &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;∆&lt;/mo&gt;\u0000 &lt;mi&gt;P&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ Delta P $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) and abnormally pressured or warning (reducing &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;∆&lt;/mo&gt;\u0000 &lt;mi&gt;P&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ Delta P $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) states respectively. State 2 is the observable failure state (from negative &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;∆&lt;/mo&gt;\u0000 &lt;mi&gt;P&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ Delta P $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and loss of well control). The signal process of the evolution of differential pressure &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;(&lt;/mo&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mo&gt;∆&lt;/mo&gt;\u0000 &lt;mi&gt;P&lt;/mi&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mo&gt;)&lt;/mo&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ left(Delta Pright) $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; is identified in the changes in the observable rate of penetration (ROP) encoded in drilling performance data. The state and observation parameters of the HMM are estimated using the Expectation Maximization (EM) algorithm and we show, for a univariate system with a depth dependent time relationship, that the model parameter updates of th","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 3","pages":"772-790"},"PeriodicalIF":1.4,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2835","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138824342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum to “An improved Hotelling's T2 chart for monitoring a finite horizon process based on run rules schemes: A Markov-chain approach”","authors":"","doi":"10.1002/asmb.2833","DOIUrl":"10.1002/asmb.2833","url":null,"abstract":"<p>This article corrects the following:</p><p>In this research paper by Chew et al.,<span>¹</span> on page 590, the funding information in the Acknowledgement is incorrect.</p><p>The correct funding information should be:</p><p>This work is funded by the Ministry of Higher Education Malaysia, Fundamental Research Grant Scheme [Grant Number: FRGS/1/2019/STG06/USM/02/5], for the project entitled “New Robust Adaptive Model for Coefficient of Variation in Infinite and Finite Horizon Processes.”</p><p>We apologise for this error.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 1","pages":"216"},"PeriodicalIF":1.4,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2833","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138692524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rejoinder to “Specifying Prior Distribution in Reliability Applications”","authors":"Qinglong Tian,&nbsp;Colin Lewis-Beck,&nbsp;Jarad B. Niemi,&nbsp;William Q. Meeker","doi":"10.1002/asmb.2832","DOIUrl":"10.1002/asmb.2832","url":null,"abstract":"<p>We response to comments on our paper “Specifying Prior Distributions in Reliability Applications” in this rejoinder.</p>","PeriodicalId":55495,"journal":{"name":"Applied Stochastic Models in Business and Industry","volume":"40 1","pages":"130-143"},"PeriodicalIF":1.4,"publicationDate":"2023-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asmb.2832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138561594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}