A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items

<!DOCTYPE html>    <html>  <head> <meta charset="utf-8" /> <title>A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items</title>  <link rel="shortcut icon" type="image/ico" href="./data/ijsom/coversheet/favicon.ico" />  <meta name="viewport" content="width=device-width, maximum-scale=1, initial-scale=1, user-scalable=0" />   <meta name="keywords" content="Robust optimization model,hospitality management,decision making under uncertainty,diet problem,food and beverage items" /> <meta name="description" content="This paper presents a simple and easy-to-use methodology for designing the menu in Food and Beverage (F&B) enterprises over a period of time, considering that certain elements of the problem are subject to uncertainty. The methodology considers both nutritional and financial aspects and allows the decision makers to explore the effect of the uncertainty on the final solutions, according to their perception of risk.The proposed methodology is based on multi-objective mixed integer programming and in particular the Almost Robust Optimization (ARO) approach introduced by Baron et al. (2019). In contrast to conventional Robust Optimization techniques, the ARO approach is more flexible and offers the decision makers the possibility to express their attitude towards risk through appropriate parameters and obtain a series of solutions corresponding to different levels of risk.The proposed model is applied in a case study concerning F&B enterprises from the island of Crete, Greece, using real data that was collected in collaboration with nutritionists and managers employed in F&B enterprises.Decision-makers in F&B enterprises may use the proposed model as a decision support tool to incorporate the inherent uncertainty into the decision-making process. Through appropriate parameters, they may select optimal diets that are feasible for most realizations of the uncertain parameters, without incurring significant increases in cost. The model is flexible and produces a series of alternative solutions based on the decision makers’ preferences and perception of risk." /> <meta name="title" content="A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items" /> <meta name="googlebot" content="NOODP" /> <meta name="citation_title" content="A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items" /> <meta name="citation_author" content="Vasilakakis, Konstantinos" /> <meta name="citation_author_institution" content="Department of Economics and Sustainable Development, School of Environment, Geography and Applied Economics, Harokopio University of Athens, Greece." /> <meta name="citation_author" content="Giannikos, Ioannis" /> <meta name="citation_author_institution" content="Department of Business Administration, University of Patras, 26500 Patras, Greece" /> <meta name="citation_abstract" content="This paper presents a simple and easy-to-use methodology for designing the menu in Food and Beverage (F&B) enterprises over a period of time, considering that certain elements of the problem are subject to uncertainty. The methodology considers both nutritional and financial aspects and allows the decision makers to explore the effect of the uncertainty on the final solutions, according to their perception of risk.The proposed methodology is based on multi-objective mixed integer programming and in particular the Almost Robust Optimization (ARO) approach introduced by Baron et al. (2019). In contrast to conventional Robust Optimization techniques, the ARO approach is more flexible and offers the decision makers the possibility to express their attitude towards risk through appropriate parameters and obtain a series of solutions corresponding to different levels of risk.The proposed model is applied in a case study concerning F&B enterprises from the island of Crete, Greece, using real data that was collected in collaboration with nutritionists and managers employed in F&B enterprises.Decision-makers in F&B enterprises may use the proposed model as a decision support tool to incorporate the inherent uncertainty into the decision-making process. Through appropriate parameters, they may select optimal diets that are feasible for most realizations of the uncertain parameters, without incurring significant increases in cost. The model is flexible and produces a series of alternative solutions based on the decision makers’ preferences and perception of risk." /> <meta name="citation_id" content="2916" /> <meta name="citation_publication_date" content="2023/11/01" /> <meta name="citation_date" content="2023-11-01" /> <meta name="citation_journal_title" content="International Journal of Supply and Operations Management" /> <meta name="citation_issn" content="23831359" /> <meta name="citation_volume" content="10" /> <meta name="citation_issue" content="4" /> <meta name="citation_firstpage" content="485" /> <meta name="citation_lastpage" content="500" /> <meta name="citation_publisher" content="Kharazmi University" /> <meta name="citation_doi" content="10.22034/ijsom.2023.109998.2806" /> <meta name="DC.Identifier" content="10.22034/ijsom.2023.109998.2806" /> <meta name="citation_abstract_html_url" content="http://www.ijsom.com/article_2916.html" /> <meta name="citation_pdf_url" content="http://www.ijsom.com/article_2916_c0efee7ff1644714cd9da5d41a1f29bc.pdf" /> <meta name="DC.Title" content="A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items" /> <meta name="DC.Source" content="International Journal of Supply and Operations Management" /> <meta name="DC.Date" content="01/11/2023" /> <meta name="DC.Date.issued" content="2023-11-01" /> <meta name="DC.Format" content="application/pdf" /> <meta name="DC.Contributor" content="Vasilakakis, Konstantinos" /> <meta name="DC.Contributor" content="Giannikos, Ioannis" /> <meta name="og:title" content="A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items" /> <meta name="og:description" content="This paper presents a simple and easy-to-use methodology for designing the menu in Food and Beverage (F&B) enterprises over a period of time, considering that certain elements of the problem are subject to uncertainty. The methodology considers both nutritional and financial aspects and allows the decision makers to explore the effect of the uncertainty on the final solutions, according to their perception of risk.The proposed methodology is based on multi-objective mixed integer programming and in particular the Almost Robust Optimization (ARO) approach introduced by Baron et al. (2019). In contrast to conventional Robust Optimization techniques, the ARO approach is more flexible and offers the decision makers the possibility to express their attitude towards risk through appropriate parameters and obtain a series of solutions corresponding to different levels of risk.The proposed model is applied in a case study concerning F&B enterprises from the island of Crete, Greece, using real data that was collected in collaboration with nutritionists and managers employed in F&B enterprises.Decision-makers in F&B enterprises may use the proposed model as a decision support tool to incorporate the inherent uncertainty into the decision-making process. Through appropriate parameters, they may select optimal diets that are feasible for most realizations of the uncertain parameters, without incurring significant increases in cost. The model is flexible and produces a series of alternative solutions based on the decision makers’ preferences and perception of risk." /> <meta name="og:url" content="http://www.ijsom.com/article_2916.html" />  <link href="./themes/base/front/assets/css/social-icon-font.css" rel="stylesheet" type="text/css" />  <link href="./themes/base/front/assets/plugins/bootstrap/css/bootstrap.min.css?v=0.02" rel="stylesheet" type="text/css" /> <link href="./themes/old/front/assets/css/header.css?v=0.05" rel="stylesheet" type="text/css" /> <link href="./themes/old/front/assets/css/footer.css" rel="stylesheet" type="text/css" /> <link href="./inc/css/essentials.css?v=0.2" rel="stylesheet" type="text/css" /> <link href="./inc/css/cookieconsent.min.css" rel="stylesheet" type="text/css" /> <link href="./inc/css/print.css" rel="stylesheet" type="text/css" media="print"/>  <link href="./themes/base/front/assets/plugins/bootstrap/css/bootstrap-ltr.min.css" rel="stylesheet" type="text/css" /> <link href=" 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href="./?_action=article&au=130340&_au=Konstantinos++Vasilakakis">Konstantinos Vasilakakis</a> <sup><a href="mailto:kvasilakakis@yahoo.gr" data-toggle="tooltip" data-placement="bottom" title="Email to Corresponding Author"><i class="fa fa-envelope-o" ></i></a></sup> <sup class="ltr"><a class=" text-green" href="https://www.orcid.org/0000-0001-6214-5692" data-toggle="tooltip" data-placement="bottom" data-html="true" title="ORCID: 0000-0001-6214-5692" target="_blank"><i class="ai ai-orcid size-13" ></i></a></sup> <sup><a href="#aff1" >1</a></sup> </li> <li class="padding-3"> <a href="./?_action=article&au=130342&_au=Ioannis++Giannikos">Ioannis Giannikos</a> <sup><a href="#aff2" >2</a></sup> </li> </ul> <p class="margin-bottom-3 ltr" id="aff1"> <sup>1</sup> Department of Economics and Sustainable Development, School of Environment, Geography and Applied Economics, Harokopio University of Athens, Greece. </p> <p class="margin-bottom-3 ltr" id="aff2"> <sup>2</sup> Department of Business Administration, University of Patras, 26500 Patras, Greece </p> <div class="margin-bottom-3 ltr" id="ar_doi" title="DOI"><i class="ai ai-doi size-25 text-orange"></i> <span dir="ltr"><a href="https://dx.doi.org/10.22034/ijsom.2023.109998.2806">10.22034/ijsom.2023.109998.2806</a></span></div> <p style="margin:12px -2px 0 -2px"><strong>Abstract</strong></p> <div class="padding_abstract justify ltr">This paper presents a simple and easy-to-use methodology for designing the menu in Food and Beverage (F&B) enterprises over a period of time, considering that certain elements of the problem are subject to uncertainty. The methodology considers both nutritional and financial aspects and allows the decision makers to explore the effect of the uncertainty on the final solutions, according to their perception of risk.<br />The proposed methodology is based on multi-objective mixed integer programming and in particular the Almost Robust Optimization (ARO) approach introduced by Baron et <em>al.</em> (2019). In contrast to conventional Robust Optimization techniques, the ARO approach is more flexible and offers the decision makers the possibility to express their attitude towards risk through appropriate parameters and obtain a series of solutions corresponding to different levels of risk.<br />The proposed model is applied in a case study concerning F&B enterprises from the island of Crete, Greece, using real data that was collected in collaboration with nutritionists and managers employed in F&B enterprises.<br />Decision-makers in F&B enterprises may use the proposed model as a decision support tool to incorporate the inherent uncertainty into the decision-making process. Through appropriate parameters, they may select optimal diets that are feasible for most realizations of the uncertain parameters, without incurring significant increases in cost. The model is flexible and produces a series of alternative solutions based on the decision makers’ preferences and perception of risk.</div> <p class="padding-0" style="margin:12px -2px 0 -2px"><strong>Keywords</strong></p> <ul class="block list-inline list-inline-seprator margin-bottom-6 ltr"> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106438&_kw=Robust+optimization+model" >Robust optimization model</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106439&_kw=hospitality+management" >hospitality management</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106440&_kw=decision+making+under+uncertainty" >decision making under uncertainty</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106441&_kw=diet+problem" >diet problem</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106442&_kw=food+and+beverage+items" >food and beverage items</a> </li> </ul> </div> <hr> <div class="page_break"></div> <div class="panel"> <div class="panel-heading card-header"> <h4 class="panel-title "> <a data-toggle="collapse" data-parent="#accordions" href="#collapsesRef"><i class="fa fa-plus"></i> References</a> </h4> </div> <div id="collapsesRef" class="panel-collapse collapse"> <div class="panel-body justify"> <div class="padding-3 margin-top-3 ltr justify">Alinezhad M., Mahdavi I., Hematian M. <em>et al.</em> (2021). 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(2023). A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items. <em>International Journal of Supply and Operations Management</em>, 10(4), 485-500. doi: 10.22034/ijsom.2023.109998.2806</p> </div> </div> </div> </div> <div id="cite-mla" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content">  <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">MLA</h4> </div>  <div class="modal-body"> <p>Konstantinos Vasilakakis; Ioannis Giannikos. "A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items". <em>International Journal of Supply and Operations Management</em>, 10, 4, 2023, 485-500. doi: 10.22034/ijsom.2023.109998.2806</p> </div> </div> </div> </div> <div id="cite-harvard" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content">  <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">HARVARD</h4> </div>  <div class="modal-body"> <p>Vasilakakis, K., Giannikos, I. (2023). 'A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items', <em>International Journal of Supply and Operations Management</em>, 10(4), pp. 485-500. doi: 10.22034/ijsom.2023.109998.2806</p> </div> </div> </div> </div> <div id="cite-vancouver" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content">  <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">VANCOUVER</h4> </div>  <div class="modal-body"> <p>Vasilakakis, K., Giannikos, I. A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items. <em>International Journal of Supply and Operations Management</em>, 2023; 10(4): 485-500. doi: 10.22034/ijsom.2023.109998.2806</p> </div> </div> </div> </div> </div> </div>   <section class="alternate padding-xxs"> </section>   <div class="container"> <footer id="footer"> <div class="scrollup" id="scroll" href="#"><span></span></div> <div class="row"> <div class="col-md-2">  <h4 class="">Explore Journal</h4> <ul class="footer-links list-unstyled"> <li id="fli_home"><a href="./">Home</a></li> <li id="fli_about"><a href="./journal/about">About Journal</a></li> <li id="fli_Edb"><a href="./journal/editorial.board">Editorial Board</a></li> <li id="fli_submit"><a href="./author">Submit Manuscript</a></li> <li id="fli_contactus"><a href="./journal/contact.us">Contact Us</a></li> <li id="fli_glossary"><a href="./journal/glossary">Glossary</a></li> <li id="fli_order_hrdj"><a href="./journal/subscription.form">Hard Copy Subscription</a></li> <li id="fli_sitemap"><a href="./sitemap.xml?usr">Sitemap</a></li> </ul>  </div> <div class="col-md-3">  <h4 class="">Latest News</h4> <ul class="footer-posts list-unstyled"> <li> <a href="./news?newsCode=173">SD of ISC: Sustainable Development of Intelligent Supply Chains based on Trends and Future Directions: Application of Novel Solution Techniques</a> <small class="ltr">2023-03-05</small> </li> </ul>  </div> <div class="col-md-3">  <div><p><a title="Linkedin" href="http://www.linkedin.com/company/ijsom?trk=eml-cp_mktg-btn-welcome-20120607%2F"><img src="images/linkedin.jpg" alt="linkedin" /></a></p></div>  </div> <div class="col-md-4">  <h4 class="">Newsletter Subscription</h4> <p>Subscribe to the journal newsletter and receive the latest news and updates</p> <form class="validate" action="" method="post" data-success="Subscription saved successfully." data-toastr-position="bottom-right"> <input type="hidden" name="_token" value="6cb542d6f46485ab05e7b8c6a4f0e4bcc98af4f6a7007ffd"/> <div class="input-group"> <span class="input-group-addon"><i class="fa fa-envelope"></i></span> <input type="email" id="email" name="email" required="required" class="form-control required sbs_email" placeholder="Enter your Email" oninvalid="this.setCustomValidity('Enter a valid email address.')" oninput="this.setCustomValidity('')"> <span class="input-group-btn"> <button class="btn btn-primary mybtn" type="submit">Subscribe</button> </span> </div> </form>   <div class="margin-top-20"> <a class="noborder" href="" target="_blank" class="social-icon social-icon-border social-facebook pull-left block" data-toggle="tooltip" data-placement="top" title="Facebook"> <i class="fa fa-facebook-square" aria-hidden="true"></i> </a> <a class="noborder" href="" target="_blank" class="social-icon social-icon-border social-facebook pull-left block" data-toggle="tooltip" data-placement="top" title="Twitter"> <i class="fa fa-twitter-square" aria-hidden="true"></i> </a> <a class="noborder" href="" target="_blank" class="social-icon social-icon-border social-facebook pull-left block" data-toggle="tooltip" data-placement="top" title="Linkedin"> <i class="fa fa-linkedin-square" aria-hidden="true"></i> </a> <a class="noborder" href="./ju.rss" class="social-icon social-icon-border social-rss pull-left block" data-toggle="tooltip" data-placement="top" title="Rss"><i class="fa fa-rss-square" aria-hidden="true"></i></a> </div> </div> </div> <div class="copyright" style="position: relative"> <ul class="nomargin list-inline mobile-block"> <li>© Journal Management System. <span id='sp_crt'>Powered by <a target='_blank' href='https://www.sinaweb.net/'>Sinaweb</a></span></li> </ul> </div> </footer> </div>  </div>   <a href="#" id="toTop_old"></a>  <div id="preloader"> <div class="inner"> <span class="loader"></span> </div> </div>  <script type="text/javascript">var plugin_path = './themes/base/front/assets/plugins/';</script> <script type="text/javascript" src="./themes/base/front/assets/js/scripts.js?v=0.02"></script>   <script type="text/javascript"> $('ul.nav li.dropdown').hover(function() { if (window.matchMedia('(max-width: 767px)').matches) return; 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A Robust Optimization Model for Determining Optimal Diets for Food and Beverage (F&B) Items