Optimal Scheduling of Waitstaff with Different Experience Levels at a Restaurant Chain

N. Akhundov, N. Tahirov, C. Glock
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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.
连锁餐厅不同经验水平服务员的最优调度
餐馆经常面临着降低成本的巨大压力。经理们的反应通常是雇用临时或兼职工人,并尽可能地减少劳动力规模,这使得很难制定一个人事安排,为客户提供充分的服务。如果(频繁的)员工流动和需求波动发生,如果员工的经验水平不同,问题就会变得更加复杂。本文提出了一个数学模型,以支持在巴库,阿塞拜疆的连锁餐厅服务员调度,考虑到公司的管理要求。我们解决的问题相当于一般的旅游日程安排问题,即分配服务员在一周内轮班工作。我们建立了三个整数规划模型,考虑员工类型和经验水平、客户订单复杂程度的差异、附带任务和责任等因素,找到最优员工人数以及每个员工的最佳行程。对模型进行了最优求解,并将结果应用于巴库一家连锁餐厅的分店。与现有的时间表相比,优化后的时间表使餐厅在保持相同的服务标准的情况下,减少了大约40%的人员过剩水平和20%的劳动力成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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