Optimal scheduling of waitstaff with different experience levels at a restaurant chain
Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customer...
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Veröffentlicht in: | INFORMS journal on applied analytics 2022-07, Vol.52 (4), p.324-343 |
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description | Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customers. The problem gets even more complicated if (frequent) employee turnover and demand fluctuations occur and if employees have different experience levels. This paper presents mathematical models to support waitstaff scheduling at a restaurant chain based in Baku, Azerbaijan, taking into account the managerial requirements of the company. The problem we address is equivalent to a general tour scheduling problem that assigns waitstaff to work shifts throughout the week. We develop three integer programming models taking account of factors, such as employee types and experience levels, differences in the complexity of customer orders, and side tasks and responsibilities, to find the optimal number of employees together with the best tour for each of them. The models are solved to optimality, and the results are applied at a branch of the restaurant chain in Baku. Compared with the existing schedule, the optimized schedule enabled the restaurant to reduce overstaffing levels by approximately 40% and labor costs by 20% while keeping the same service standards.
Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customers. The problem gets even more complicated if (frequent) employee turnover and demand fluctuations occur and if employees have different experience levels. This paper presents mathematical models to support waitstaff scheduling at a restaurant chain based in Baku, Azerbaijan, taking into account the managerial requirements of the company. The problem we address is equivalent to a general tour scheduling problem that assigns waitstaff to work shifts throughout the week. We develop three integer programming models taking account of factors, such as employee types and experience levels, differences in the complexity of customer orders, and side tasks and responsibilities, to find the optimal number of employees together with the best tour for each of them. The models are solved to optimality, and the results are applied |
doi_str_mv | 10.1287/inte.2022.1124 |
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Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customers. The problem gets even more complicated if (frequent) employee turnover and demand fluctuations occur and if employees have different experience levels. This paper presents mathematical models to support waitstaff scheduling at a restaurant chain based in Baku, Azerbaijan, taking into account the managerial requirements of the company. The problem we address is equivalent to a general tour scheduling problem that assigns waitstaff to work shifts throughout the week. We develop three integer programming models taking account of factors, such as employee types and experience levels, differences in the complexity of customer orders, and side tasks and responsibilities, to find the optimal number of employees together with the best tour for each of them. The models are solved to optimality, and the results are applied at a branch of the restaurant chain in Baku. Compared with the existing schedule, the optimized schedule enabled the restaurant to reduce overstaffing levels by approximately 40% and labor costs by 20% while keeping the same service standards.</description><identifier>ISSN: 2644-0865</identifier><identifier>EISSN: 2644-0873</identifier><identifier>DOI: 10.1287/inte.2022.1124</identifier><language>eng</language><publisher>Catonsville: Institute for Operations Research and the Management Sciences</publisher><subject>Chain branching ; Chain stores ; Cost control ; Customers ; Employee turnover ; Employees ; Hiring ; Human resource management ; Integer programming ; Labor costs ; Mathematical models ; Optimization ; Restaurants ; Schedules ; Scheduling ; Shift work ; Staffing ; Task complexity ; Workforce ; Workforce planning</subject><ispartof>INFORMS journal on applied analytics, 2022-07, Vol.52 (4), p.324-343</ispartof><rights>Copyright Institute for Operations Research and the Management Sciences Jul/Aug 2022</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c324t-66f14f27a4e60dde177fbee5355d01bb4b9091c9c2bcf6d1591e202d296f84e43</citedby><cites>FETCH-LOGICAL-c324t-66f14f27a4e60dde177fbee5355d01bb4b9091c9c2bcf6d1591e202d296f84e43</cites><orcidid>0000-0002-8011-8097 ; 0000-0003-4287-7532 ; 0000-0001-6006-0070</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3690,27923,27924</link.rule.ids></links><search><creatorcontrib>Akhundov, Najmaddin</creatorcontrib><title>Optimal scheduling of waitstaff with different experience levels at a restaurant chain</title><title>INFORMS journal on applied analytics</title><description>Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customers. The problem gets even more complicated if (frequent) employee turnover and demand fluctuations occur and if employees have different experience levels. This paper presents mathematical models to support waitstaff scheduling at a restaurant chain based in Baku, Azerbaijan, taking into account the managerial requirements of the company. The problem we address is equivalent to a general tour scheduling problem that assigns waitstaff to work shifts throughout the week. We develop three integer programming models taking account of factors, such as employee types and experience levels, differences in the complexity of customer orders, and side tasks and responsibilities, to find the optimal number of employees together with the best tour for each of them. The models are solved to optimality, and the results are applied at a branch of the restaurant chain in Baku. Compared with the existing schedule, the optimized schedule enabled the restaurant to reduce overstaffing levels by approximately 40% and labor costs by 20% while keeping the same service standards.
Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customers. The problem gets even more complicated if (frequent) employee turnover and demand fluctuations occur and if employees have different experience levels. This paper presents mathematical models to support waitstaff scheduling at a restaurant chain based in Baku, Azerbaijan, taking into account the managerial requirements of the company. The problem we address is equivalent to a general tour scheduling problem that assigns waitstaff to work shifts throughout the week. We develop three integer programming models taking account of factors, such as employee types and experience levels, differences in the complexity of customer orders, and side tasks and responsibilities, to find the optimal number of employees together with the best tour for each of them. The models are solved to optimality, and the results are applied at a branch of the restaurant chain in Baku. Compared with the existing schedule, the optimized schedule enabled the restaurant to reduce overstaffing levels by approximately 40% and labor costs by 20% while keeping the same service standards.</description><subject>Chain branching</subject><subject>Chain stores</subject><subject>Cost control</subject><subject>Customers</subject><subject>Employee turnover</subject><subject>Employees</subject><subject>Hiring</subject><subject>Human resource management</subject><subject>Integer programming</subject><subject>Labor costs</subject><subject>Mathematical models</subject><subject>Optimization</subject><subject>Restaurants</subject><subject>Schedules</subject><subject>Scheduling</subject><subject>Shift work</subject><subject>Staffing</subject><subject>Task complexity</subject><subject>Workforce</subject><subject>Workforce planning</subject><issn>2644-0865</issn><issn>2644-0873</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNpFkEtPwzAQhCMEElXplbMlzgm240d8RBUvqVIvwNVynDV1FZJgOzz-Pa6K4LRz-GZ3dorikuCK0EZe-yFBRTGlFSGUnRQLKhgrcSPr0z8t-HmxinGPMaaESM74onjZTsm_mR5Fu4Nu7v3wikaHPo1PMRmXlU871HnnIMCQEHxNEDwMFlAPH9BHZBIyKECm52AyYXfGDxfFmTN9hNXvXBbPd7dP64dys71_XN9sSltTlkohHGGOSsNA4K4DIqVrAXjNeYdJ27JWYUWssrS1TnSEKwL5yY4q4RoGrF4WV8e9Uxjf5xxC78c5DPmkpkJxThThdaaqI2XDGGMAp6eQnw7fmmB9qE8f6tOH-vShvmxARwPYcfDxH28IlzmSkvUPh-luVA</recordid><startdate>20220701</startdate><enddate>20220701</enddate><creator>Akhundov, Najmaddin</creator><general>Institute for Operations Research and the Management Sciences</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>JQ2</scope><orcidid>https://orcid.org/0000-0002-8011-8097</orcidid><orcidid>https://orcid.org/0000-0003-4287-7532</orcidid><orcidid>https://orcid.org/0000-0001-6006-0070</orcidid></search><sort><creationdate>20220701</creationdate><title>Optimal scheduling of waitstaff with different experience levels at a restaurant chain</title><author>Akhundov, Najmaddin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c324t-66f14f27a4e60dde177fbee5355d01bb4b9091c9c2bcf6d1591e202d296f84e43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Chain branching</topic><topic>Chain stores</topic><topic>Cost control</topic><topic>Customers</topic><topic>Employee turnover</topic><topic>Employees</topic><topic>Hiring</topic><topic>Human resource management</topic><topic>Integer programming</topic><topic>Labor costs</topic><topic>Mathematical models</topic><topic>Optimization</topic><topic>Restaurants</topic><topic>Schedules</topic><topic>Scheduling</topic><topic>Shift work</topic><topic>Staffing</topic><topic>Task complexity</topic><topic>Workforce</topic><topic>Workforce planning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Akhundov, Najmaddin</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Computer Science Collection</collection><jtitle>INFORMS journal on applied analytics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Akhundov, Najmaddin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal scheduling of waitstaff with different experience levels at a restaurant chain</atitle><jtitle>INFORMS journal on applied analytics</jtitle><date>2022-07-01</date><risdate>2022</risdate><volume>52</volume><issue>4</issue><spage>324</spage><epage>343</epage><pages>324-343</pages><issn>2644-0865</issn><eissn>2644-0873</eissn><abstract>Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customers. The problem gets even more complicated if (frequent) employee turnover and demand fluctuations occur and if employees have different experience levels. This paper presents mathematical models to support waitstaff scheduling at a restaurant chain based in Baku, Azerbaijan, taking into account the managerial requirements of the company. The problem we address is equivalent to a general tour scheduling problem that assigns waitstaff to work shifts throughout the week. We develop three integer programming models taking account of factors, such as employee types and experience levels, differences in the complexity of customer orders, and side tasks and responsibilities, to find the optimal number of employees together with the best tour for each of them. The models are solved to optimality, and the results are applied at a branch of the restaurant chain in Baku. Compared with the existing schedule, the optimized schedule enabled the restaurant to reduce overstaffing levels by approximately 40% and labor costs by 20% while keeping the same service standards.
Restaurants often face strong pressure to reduce costs. Managers regularly respond by hiring temporary or part-time workers and by trying to reduce the size of the workforce as much as possible, which makes it difficult to develop a personnel schedule that provides sufficient service to the customers. The problem gets even more complicated if (frequent) employee turnover and demand fluctuations occur and if employees have different experience levels. This paper presents mathematical models to support waitstaff scheduling at a restaurant chain based in Baku, Azerbaijan, taking into account the managerial requirements of the company. The problem we address is equivalent to a general tour scheduling problem that assigns waitstaff to work shifts throughout the week. We develop three integer programming models taking account of factors, such as employee types and experience levels, differences in the complexity of customer orders, and side tasks and responsibilities, to find the optimal number of employees together with the best tour for each of them. The models are solved to optimality, and the results are applied at a branch of the restaurant chain in Baku. Compared with the existing schedule, the optimized schedule enabled the restaurant to reduce overstaffing levels by approximately 40% and labor costs by 20% while keeping the same service standards.</abstract><cop>Catonsville</cop><pub>Institute for Operations Research and the Management Sciences</pub><doi>10.1287/inte.2022.1124</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-8011-8097</orcidid><orcidid>https://orcid.org/0000-0003-4287-7532</orcidid><orcidid>https://orcid.org/0000-0001-6006-0070</orcidid></addata></record> |
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subjects | Chain branching Chain stores Cost control Customers Employee turnover Employees Hiring Human resource management Integer programming Labor costs Mathematical models Optimization Restaurants Schedules Scheduling Shift work Staffing Task complexity Workforce Workforce planning |
title | Optimal scheduling of waitstaff with different experience levels at a restaurant chain |
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