Multi-stove Scheduling Model And Algorithm With Mergeable Products

Takeout has now been integrated into everyone's life.More and more traditional catering enterprises choose to expand their sales channels by joining the takeout platform.Online ordering involves preparation and delivery.The process starts when an order arrives.The restaurant needs to receive the order in time and schedule the preparation of dishes.The courier will then pick up the prepared dishes and deliver them to corresponding customers.Existing practical and academic research pays particular attention to the delivery process.For instance,takeout route planning models and continuous optimization of algorithms are studied in order to improve the efficiency of delivery processes.To ease the tension of transportation capacity,part-time couriers convene through crowd-sourcing and are added to the distribution system during peak hours.To ensure the speed of distribution and sufficient capacity,the takeout platforms are devoted to finding an appropriate reward system.These efforts contribute to the efficient capacity of the delivery process.However,compared with the delivery process,the food preparing process is harder to adjust during peak periods because of poor flexibility.Often during peak meal hours,catering enterprises have to face the dual pressure of online orders and in store customers while ensuring the quality of dishes.If online orders cannot be completed in time,they will not only be complained by riders,reminders and complaints from online customers,but also affect the in store experience of offline customers,Bring satisfaction to the restaurant and reduce the risk of losing customers.Therefore,how to arrange the cooking sequence of the back kitchen during the peak meal period and complete the meal delivery in time is a difficult problem that catering enterprises need to solve in the process of expanding the market.The main work of this paper has two aspects.First,aiming at the goal of catering enterprises to "shorten the meal delivery time,improve customer satisfaction and achieve revenue growth",according to the characteristics of "multiple stoves work at the same time,orders contain multiple dishes,and the same dishes can be combined and processed" in the restaurant meal delivery scheduling,a two-tier scheduling model with the goal of order completion time satisfaction rate is constructed,The upper layer is the order selection model,and the lower layer is the vegetable package processing scheduling model.A numerical example is designed for comparison and test.Second,the static model is extended to the real scene of dynamic scheduling.In order to ensure the solution efficiency of the model and facilitate the differentiation of food packages processed on different stoves,this paper adopts the design idea of piecewise coding and designs a targeted genetic algorithm.The experimental results show that the genetic algorithm is better than the heuristic strategy of the most urgent dishes first,the longest processing time first and the most popular dishes.The scheduling method of this model has the highest order completion rate and the shortest timeout time.The results show that the stove scheduling model in peak dining hours can reduce the idle time of the stove in the production process of the restaurant and the time for the distributor to wait for the merchant to have a meal after arriving at the store.This can save natural gas and the power consumption of battery cars.At the same time,this scheduling method can better help catering enterprises realize their social responsibility,that is,to ensure that meal orders are completed on time and avoid employees working too long in high-temperature kitchens.Therefore,the scheduling model proposed in this paper has a certain reference and reference significance for the catering industry.