Meal Order Research Articles

Dietary Approaches for Complementary Feeding: The Greek Mediterranean Diet as a Model for Caregivers

Background/Objectives: Complementary feeding (CF), is defined as the process of providing foods in addition to milk when breast milk or milk formula alone are no longer adequate to meet nutritional requirements. CF affects not only growth but also the subsequent development of the child’s dietary preferences. The Mediterranean diet (MedDiet) is one of the most studied dietary patterns worldwide. The main purpose of this article is to provide practical guidance for CF to caregivers introducing the Greek MedDiet, summarizing the current different approaches. The evidence-based information provided could be used by developers to create a reliable digital app for CF based on Mediterranean foods and traditional dishes. Methods: An in-depth literature review of the existing guidelines and recently published research data on CF using PubMed, national recommendations, and grey literature were undertaken. Results: Practical, simple, evidence-based, comprehensive tables are presented. The tables serve as a guide to simplify the process of introducing Mediterranean foods in CF. Τhe tables consist of a total of more than 90 foods and day-to-day guidance for the first 13 weeks of CF. Furthermore, specific dietary guidance and suggestions regarding the order and content of meals during CF are given. Discussion: The tables are based on updated recommendations, summarizing the optimal feeding practices in a MedDiet-based perspective. Conclusions: Conclusively, there are significant contradictions among different organizations that present practical issues and cause confusion among caregivers. An effort was carried out to provide practical evidence-based guidance for caregivers introducing MedDiet during CF.

Differences in eating behaviours and mothers attitudes between baby-led weaning vs. traditional spoon-feeding approaches in Turkiye

This study was aimed to examine the differences in eating behaviours and mothers attitudes between baby-led vs. traditional spoon-feeding approaches and its effect on eating behaviours in preschool children. The study was conducted with 150 mothers of children aged 2–6, who applied to the Pediatrics Polyclinic of Başkent University Ankara Hospital, between December 2022 and February 2023. Sociodemographics, biochemical parameters were recorded to form. Maternal attitudes and eating behaviours of children were evaluated with Mother's Attitudes Towards the Feeding Process Scale (MATFP) and Early Childhood Adaptive Eating Behaviour Scale (ECAEB), respectively. The mean age of the children was 43.80 ± 11.04 months and 51.3% of them were girls. A weak negative correlation was found between the ECAEB total scores and the child age (r = −0.196, p < 0.05). A moderate positive correlation was found between the total scores of the MATFP and ECAEB (r = 0.699, p < 0.001). There wasn't significant difference between the MATFP total scores who chose baby-led weaning or traditional feeding (p > 0.05). According to the ECAEB; aggression and reaction to main meal order subgroup scores of children who consumed pureed vegetables until the ninth month were higher than those who didn't consume them (p < 0.05). Mothers who prefer the TSF offer their babies more blenderized and pureed foods, while those who prefer the BLW serve fork-mashed, steamed and sliced foods (p < 0,05). As the mothers‘ subscale scores for negative affect during meals, attitudes about insufficient/unbalanced feeding, negative feeding strategies, forced feeding, reaction to viewpoint of others increase, so did their subscale scores for child reluctance, eating refusal associated with sensory causes, aggression, reaction to main meal order increase. Consequently, it's believed that maternal attitudes and actions should be taken into account while evaluating the eating habits of toddlers.

All On One Page: Getting Daily Meal Ordering Right In A Rehabilitation Setting

Abstract Background Recently the rehabilitation hospital expanded to over 100 beds providing improved access to rehabilitation for older persons in the area. During this time, an increase in incident report forms occurred due to the incorrect provision of diet/fluid to patients at ward level. In collaboration with relevant stakeholders, the Speech and Language Therapy (SLT) and Dietetic teams reviewed the current hospital meal ordering form and process in order to standardise a new system. The aim of this project was to reduce risk for patients and improve collaborative team working and communication. Methods A multidisciplinary team (MDT) approach was adapted involving; SLT, dietitians, catering department, nursing team and the patient quality and safety department. The HSE change framework provided scaffolding for this work. A new Daily Meal Order form was created and approved by the Nutrition Steering Committee and the process was agreed using input from all stakeholders. A pilot was carried out, reviewed and rolled out across the campus. The number of incidents recorded at ward level was used to measure if risk was reduced. A staff survey was conducted to gather feedback on the new system. Results The new Daily Meal Order form is now being used across the campus. Additional checks are completed each day via email to reduce the risk of errors. No incident reports were filed since launching the new form and process. A staff survey showed that all staff feel the new system and form constitutes an improvement, that it saves clinical time and that they would recommend it to others. Conclusion The project aims have been met in reducing patient risk, in line with the HIQA Safer Better Healthcare Programme. It has also improved MDT working and communication. This project is easily replicable to other settings and staff would recommend this approach to others.

Choice architecture promotes sustainable choices in online food-delivery apps.

Greenhouse gas emissions from the food system constitute about one-third of the global total, hence mitigation in this sphere of human activity is a vital goal for research and policy. This study empirically tests the effectiveness of different interventions to reduce the carbon footprint of food choices made on food-delivery apps, using an incentive-compatible online randomized controlled trial with 4,008 participants. The experiment utilized an interactive web platform that mimics popular online food-delivery platforms (such as Just Eat) and included three treatment conditions: a sign-posted meat tax, a carbon-footprint label, and a choice-architecture intervention that changed the order of the menu so that the lowest carbon-impact restaurants and dishes were presented first. Results show that only the choice-architecture nudge significantly reduced the average meal carbon footprint-by 0.3 kg/CO2e per order (12%), driven by a 5.6 percentage point (13%) reduction in high-carbon meal choices. Moreover, we find evidence of significant health and well-being co-benefits. Menu repositioning resulted in the average meal order having greater nutritional value and fewer calories, whilst significantly increasing self-reported satisfaction with the meal choice. Simple back-of-the-envelope calculations suggest that menu repositioning would be a highly cost-effective policy instrument if implemented at scale, with the return on investment expected to be in the range of £1.28 to £3.85 per metric ton of avoided CO2 emissions, depending on implementation costs.

On-Demand Meal Delivery: A Markov Model for Circulating Couriers

On-demand meal delivery has become a feature of most cities around the world as a result of platforms and apps that facilitate it as well as the pandemic, which for a period, closed restaurants. Meals are delivered by couriers, typically on bikes, e-bikes, or scooters, who circulate collecting meals from kitchens and delivering them to customers, who usually order online. A Markov model for circulating couriers with n + 1 parameters, where [Formula: see text] is the number of kitchens plus customers, is derived by entropy maximization. There is one parameter for each kitchen and customer representing the demand for a courier, and there is one parameter representing the urgency of delivery. It is shown how the mean and variance of delivery time can be calculated once the parameters are known. The Markov model is irreducible. Two procedures are presented for calibrating model parameters on a data set of orders. Both procedures match known order frequencies with fitted visit probabilities; the first inputs an urgency parameter value and outputs mean delivery time, whereas the second inputs mean delivery time and outputs the corresponding urgency parameter value. Model calibration is demonstrated on a publicly available data set of meal orders from Grubhub. Grubhub data are also used to validate the calibrated model using a likelihood ratio. By changing the location of one kitchen, it is shown how the calibrated model can estimate the resulting change in demand for its meals and the corresponding mean delivery time. The Markov model could also be used for the assignment of courier trips to a street network. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT Conference.

Waiting Strategy for the Dynamic Meal Delivery Routing Problem with Time-Sensitive Customers Using a Hybrid Adaptive Genetic Algorithm and Adaptive Large Neighborhood Search Algorithm

In this paper, we study the dynamic meal delivery routing problem (MDRP) with time-sensitive customers. The multi-objective MDRP optimization model is developed to maximize customer satisfaction and minimize delay penalty cost and riding cost. To solve the dynamic MDRP, a novel waiting strategy is proposed to divide the dynamic problem into a series of static subproblems. This waiting strategy utilizes the decision threshold to determine rerouting points based on the number of dynamic meal orders. Meanwhile, time-sensitive priority is introduced to accelerate assignment and routing decisions for orders from customers with high time sensitivity. For each static subproblem, a hybrid AGA–ALNS algorithm that incorporates the adaptive genetic algorithm and adaptive large neighborhood search is developed to improve both the global and local search capabilities of the genetic algorithm. We validate the performance of the proposed waiting strategy and the AGA–ALNS algorithm through numerical instances. In addition, managerial insights are obtained from sensitivity analysis experiments.

Glycemic Response And Satiety in Healthy Korean Adults Following Consumption of Equal Volumes of Pressure and Non-Pressure Rice

This study examined the effect of the same volume of pressure-cooked or non-pressure-cooked rice on the glycemic response and satiety of 28 healthy Korean adults aged 20–57 years in a randomized cross-over design. On separate mornings, all participants were served with rice that was cooked either with pressure or without pressure and side dishes in a random order. The pressure-cooked rice contained approximately 14% more energy than the non-pressure-cooked rice. The capillary blood glucose response and satiety score were measured every 15 or 30 minutes for 2 hours (3 hours for satiety) before and after consuming the meal. The glucose response was not significantly different between the meals. The feelings of hunger and fullness and prospective food consumption after eating the meals were not significantly different after adjusting for age, BMI, meal order and fasting value on the given trial day. This study suggests that consuming of equal volume of pressure or non-pressure-cooked rice may make a small difference in energy intake without affecting satiety.

Factors affecting consumer intentions and actual behavior: A case of food delivery applications

Customers and food vendors communicate directly through mobile devices. Consumers easily purchase pre-prepared meals via food delivery applications, no matter where they are, even at the convenience of their residences. Therefore, this paper aims to analyze the determinants that affect customers’ propensity to purchase and their actual behavior in the setting of food delivery applications. The impact that subjective norms have on consumers’ attitudes toward food ordering via food delivery applications is also examined. The theory of reasoned action and prospect theory are the two basic theories that this study draws on. A convenience sample approach was used to gather data from 288 consumers in Vietnam who placed meal orders using food delivery applications. The data collection was conducted using Google Forms. The results indicated that consumers’ attitude toward purchasing food via food delivery applications positively influenced their buying propensity (β = 0.191, p = 0.001). Similarly, the findings also highlighted that consumers’ subjective norm positively affected both their attitude (β = 0.417, p = 0.000) and their inclination to purchase (β = 0.258, p = 0.000). Likewise, discount framing emerged as the most influential factor affecting purchase intentions (β = 0.262, p = 0.000). Furthermore, customers’ intentions significantly contributed to their actual behavior in acquiring pre-prepared meals through food delivery applications (β = 0.556, p = 0.000). Ultimately, the study offered suggestions for executives, identified limits, and proposed avenues for future research. AcknowledgmentThe author acknowledges Industrial University of Ho Chi Minh City that supported this study.

Are postprandial glucose responses sufficiently person-specific to use in personalized dietary advice? Design of the RepEAT study: a fully controlled dietary intervention to determine the variation in glucose responses.

An elevated postprandial glucose response is associated with an increased risk of cardiometabolic diseases. Existing research suggests large heterogeneity in the postprandial glucose responses to identical meals and food products between individuals, but the effect of other consumed meals during the day and the order of meals during the day on the heterogeneity in postprandial glucose responses still needs to be investigated. In addition, the robustness of the glucose responses to meals or foods is still unknown. The overall aim of the project is to assess whether the glucose response to a meal is sufficiently person-specific to use in personalized dietary advice. We aim to answer the question: "How replicable are glucose responses to meals within individuals and how consistent is the variation in glucose responses between individuals?" The question will be assessed under standardized conditions of a 9-week fully controlled dietary intervention in which all meals are the same between individuals and consumed in a fixed order at a fixed time. 63 apparently healthy men and women with a BMI of 25-40 kg/m2 and aged 45-75 years were enrolled in the RepEAT study (NCT05456815), of whom 53 participants completed the study. The RepEAT study comprised a fully controlled dietary intervention of nine weeks, consisting of three repetitive periods of three weeks. Within each three-week period, a variety of meals and food products were offered during breakfast, lunch, dinner and in between meal snacks. Throughout the dietary intervention, glucose was continuously monitored using Freestyle Libre Pro IQ monitors. Physical activity was monitored using the ActiGraph and ActivPAL. To measure the association between glucose responses and an individual's phenotype, various measurements were performed before the start of the dietary intervention including an oral glucose tolerance test, a high-fat mixed meal challenge, assessment of body fat distribution including liver fat (MRI/MRS), and cardiometabolic markers. The repetitive and fully controlled nature of the dietary study allows detailed assessment of the replicability of the glucose responses to meals and food products within individuals. Furthermore, the consistency of the variation between individuals independent of insulin resistance will be determined.

ShopWisely - The Ultimate Price Comparer

Abstract: Customers are faced with an abundance of options in the quickly changing world of online shopping and food delivery, which makes it difficult and time-consuming to find the best offers and affordable solutions. ShopWisely has come to light as a trailblazing answer to this problem, providing consumers with a thorough platform for comparing costs from top e-commerce sites like Amazon and Flipkart as well as popular meal delivery services like Zomato and Swiggy. ShopWisely is an online project that makes it easy for people to make educated purchases. It accomplishes this by compiling real-time pricing information from several sources, giving consumers a comprehensive picture of their choices. With an attractive and userfriendly design, the platform's main objective is to expedite the online shopping and meal ordering process, eventually

A Survey Paper on Tiffindia - An Android Application for On-Demand Food

Abstract: Online meal ordering and delivery services are expanding quickly thanks to developing technology because of changes in consumer behavior and technological advancements. The way that Indian consumers have responded to the Internet has created opportunities for a wide range of enterprises, from startups to major multinationals. Businesses now have the chance to grow their online services, such as online meal ordering and delivery services, thanks to online banking. The demands of those who lead hectic lives are satisfied by online meal ordering, which allows customers to place orders using laptops, tablets, or smartphones and have their food delivered to their homes in a matter of minutes. But there aren't many platforms that provide nutritious meals, particularly for people on particular diets. Due to their hectic schedules, the majority of students end up ordering junk food online or struggle to find the right meals for their particular diet online. The "tiffin-India-app" is an online ordering and delivery system for healthy food that is suggested for Higher Education Institutions to offer staff and students a variety of healthy food alternatives that can be tailored to their individual diets. The online ordering and delivery system will be developed using an extreme programming technique. The results showed that the suggested method, which makes use of the improved web service, is a successful effort to encourage students and employees of higher education institutions to lead healthy lifestyles and adopt appropriate eating habits. I

Interactive effects of social norms and information framing on consumers' willingness of food waste reduction behavior

Nudge theory is the underpinning theory of this paper, which is used to propose the information nudge strategy for reducing food waste on the consumption stage. To achieve desired outcomes, a 2 (Social Norms: Descriptive norms vs. Injunctive norms) × 2 (Information framing: Positive framing vs. Negative framing) × 2 (Dining Scenarios: Business banquets vs. Friends and family gatherings) between-subjects experimental design was employed, based on the framing effect and the focus theory of normative conduct. Specifically, building upon prior work in behavioral economics, this paper explores the ‘match-up ’effects between social norms and information framing on consumers' willingness to reduce food waste, considering the mediating role of portion control inspiration and the moderating role of dining scenarios. Results suggest that negative-framed messages are more effective combined with injunctive norms, while positive-framed messages work better combined with descriptive norms. Noticeably, the negative-descriptive norms have the backfire effect, that is, exacerbating individuals' food waste. The dining scenarios(business banquets vs. family/friends gatherings)influence these effects. Overall, this work contributes to the literature on nudge theory and the focus theory of normative conduct by investigating how information nudge strategies can be used to promote rational meal ordering and food waste reduction at social and enterprise levels.

Is meal order timing and flexibility key to improving patient satisfaction with hospital foodservice?

The aim of this study was to retrospectively evaluate and compare patient foodservice (FS) satisfaction using a validated tool and consistent methodology in an acute health service for four different FS models as the organisation transitioned through traditional model (TM), choice at point of service (CaPOS), bedside menu ordering systems (BMOS) and room service (RS) from 2013 to 2016. Patient satisfaction data were collected using the Acute Care Hospital Foodservice Patient Satisfaction Questionnaire. For the purposes of this study, patients' rating of their overall experience with FS (very good, good, okay, poor or very poor) was compared for each site and model. Satisfaction was significantly higher in the CaPOS and RS models compared with TM. BMOS, although somewhat higher, was not shown to be significantly higher than TM. The RS model was significantly higher than BMOS, but there was no significant difference observed between RS and CaPOS. FS models that support patient flexibility and meal ordering closer to the meal delivery time (as seen with RS and CaPOS) show higher patient satisfaction among hospital patients. It is recommended that sites consistently opt to include patient satisfaction as part of routine auditing. This would enable clear conclusions to be drawn regarding best practice FS models, based on specific and individual hospital requirements.

Thinking through norms can make them more effective. Experimental evidence on reflective climate policies in the UK

Adopting low-carbon diets is important to meet our climate goals. Prior experimental evidence suggests green nudges help people adopt such diets, more so when encouraged to think through them. In this paper, we re-evaluate this role of reflection in a “social norm” nudge to promote intentions for climate-friendly diets in the United Kingdom. Using 5,555 English respondents, we find that the social norm nudge increases meal order intentions for low-carbon diets versus the control condition. Asking people to reveal their personal dietary norms after exposing them to these social norms (“lower-order nudge+”) does not produce any measurable change compared to the nudge. However, when people are subsequently encouraged to think and pledge to climate-friendly diets (“higher-order nudge+”), the effectiveness of the social norm nudge increases by 90% or more.

Anticipating Consumer Demand using ML

Abstract: Demand forecasting is essential for every growing online business. Without efficient demand forecasting systems in place, it might be next to impossible to always have the right amount of stock on hand. Because a food delivery service deals with a high volume of perishable raw materials, it is critical for the company to accurately forecast daily and weekly demand. If a warehouse has too much inventory, there is a greater likelihood of wastage, and if it has too little, there may be shortages, which would encourage customers to turn to your competitors. Therefore, predicting demand is one of the important tasks to be done. The project represents a food delivery company that operates in multiple cities. This particular company has various fulfillment centres in these cities for dispatching meal orders to their customers. Its objective is to anticipate consumer demand and the goal is to build a predictive regression model to assist the client in projecting demand for the following weeks so that these centres can organize their raw material stock properly, with the usage of various Machine Learning and Deep Learning Models and Techniques. For that purpose, there are various tools, techniques and methods are proposed. Linear regression model, Random Forest, XG Boosting, Decision tree is some of the models performed for getting the highest accuracy.

Adherence to Healthy Default Beverage Laws for Children's Meals in 3 U.S. Cities

Healthy default beverage laws are relatively new interventions designed to improve the healthfulness of children's meals in restaurants. In this study, researchers assessed adherence to healthy default beverage laws among children's meals ordered online in Los Angeles (California statewide law effective from September 2018), Baltimore (effective from April 2018), and New York City (effective from April 2019) compared with that in Boston, where no law existed. Between November and December 2020, researchers ordered children's meals from online ordering platforms (e.g., GrubHub, Uber Eats) from the top-grossing restaurant chains in each location (n=337 meal orders from 106 restaurants), coded these meals using four successively stricter definitions of adherence to the default beverage laws in each respective jurisdiction, and then applied each law to data collected in Boston to simulate different policy scenarios in a city with no such law. The team analyzed these data in late 2021. Differences in adherence existed across jurisdictions, with 15% adherent in Los Angeles, 30% in Baltimore, and 43% in New York City, compared with 7%-30% in Boston, using the most lenient definition of adherence. Fewer than 3% of all meals adhered to laws when applying the strictest definition of adherence. Overall adherence was low and variable across jurisdictions. Adherence may be lower in jurisdictions with fewer allowable default beverages, although more research is needed to assess this potential causal relation. In addition to increased resources and support for restaurants, additional policy design considerations may be necessary to increase adherence to healthy default beverage laws.

Sodium intake trend and current intake level by meal provision place among the citizens of Seoul.

The diversity of meal provision places has increased in recent years and sodium intake can vary depending on where meals are eaten, particularly in large cities. In this study, an analysis of the recent trends in sodium intake was performed and a comparison of sodium intake level according to meal provision place among citizens of Seoul was performed. Data from a 24-h recall dietary intake survey from the 2010-2019 Korea National Health and Nutrition Examination Survey (KNHANES) were used in order to determine the trends in sodium intake among citizens of Seoul, aged 3-74 years old. (n = 11,811). The trend of daily sodium intake was presented in absolute amount and proportion compared to the chronic disease risk reduction intake (CDRR) for each selected characteristic. A comparison of sodium intake level according to meal provision place by sex and age groups as a total amount per meal (mg), density per meal (mg/1,000 kcal), and proportion of the daily sodium intake was performed using the 2016-2019 KNHANES. Sodium intake levels showed a downward trend from 2010-2019. The highest level of sodium intake was observed for subjects aged 30-49, and the level for males aged 30-49 was 202.8% higher than the CDRR. Results of the analysis of sodium intake per meal according to meal provision place showed that the highest sodium intake was in the order of restaurant meal (RM) > institutional foodservice (IF) > home meal (HM) > convenience food (CF). A higher sodium density (mg/1,000 kcal) was observed for IF compared with RM in most adults. Adults aged over 50 years old consumed more than half of the daily sodium in HM. Significant variation in the level of sodium intake was observed according to sex and age groups, therefore, different approaches and nutrition policies based on meal provision place are needed.

Sensory preferences and requirements amongst Swedish older adults with motoric eating difficulties.

Finger foods, foods that can be eaten without cutlery, may be a strategy to increase autonomy and food intake amongst older adults with motoric eating difficulties. In order to develop optimal finger foods, knowledge about sensory preferences and requirements in the target population is needed. To assess sensory preferences and requirements amongst Swedish older adults with motoric eating difficulties. Check-all-that-apply (CATA), a methodology that does not require much cognitive effort, was used to collect survey data about sensory preferences and requirements for everyday meals from 15 older adults with motoric eating difficulties. The CATA-questionnaire was structured according to the Swedish meal order (breakfast, lunch, dinner, snack and fika) and consisted of 29 attributes compiled through a literature review. Through both qualitative and quantitative data analysis, it was found that flavourful, flavour intensity, spicy and both Swedish and ethnic flavours were important attributes related to food flavour. Although most participants preferred crispy and coarse textures, a few participants found soft, smooth and fine textures important. Moreover, colourful meals and serving components separated on the plate were important for the appearance of lunch and dinner. A diverse range of flavours, flavour enhancement and a balance between the basic tastes and spiciness may increase the flavour perception. Finger foods should be offered in the full range of flavours available to the general older adults' population. The variation in the demand for texture may be related to chewing and swallowing difficulties, and textures that require moderate chewing and easy swallowing are, therefore, optimal for finger foods. Separating meal components on the plate may make it easier to distinguish the components. Chemosensory impairments, chewing and swallowing difficulties, and visual disturbances are important to consider in the development of finger foods.

Two-Stage Solution for Meal Delivery Routing Optimization on Time-Sensitive Customer Satisfaction

The online-to-offline (O2O) meal delivery mode in which takeout meals are ordered online and delivered offline is recently emerging. The fast delivery of huge meal orders for time-sensitive customers imposes great challenges on O2O meal delivery platforms. This study establishes a two-stage solution for meal delivery routing optimization with the objective of maximizing time-sensitive customer satisfaction. In the first stage, a large number of meal orders are hierarchically classified and merged into delivery bundles based on the nearest pickup location rule by applying the hierarchical agglomerative clustering (HAC) algorithm, to increase fast meal delivery efficiency. In the second stage, a genetic algorithm (GA) is applied to solve the cluster-based delivery routing optimization model to find an optimal delivery route for meal orders in each delivery bundle. The numerical simulation results verify that the two-stage routing optimization solution is effective to schedule timely meal delivery and improve customer time satisfaction. The comparison of the results indicates the superiority of the proposed two-stage solution with HAC and GA on customer satisfaction while ensuring the delivery of all orders within 60 minutes. The sensitivity analysis shows the impact of time-sensitive customer heterogeneity on meal delivery satisfaction. This research has significant managerial insights for fast delivery services of O2O meal delivery platforms.

Meal delivery routing optimization with order allocation strategy based on transfer stations for instant logistics services

The rapid development of instant logistics services has brought not only convenience to people's life but also a great challenge to traffic management. Due to the limited delivery range of instant delivery systems, customers are usually recommended the meals nearby or pay much higher delivery fees for long-distance delivery. This study proposes a novel order splitting strategy based on transfer stations for long-distance meal orders to satisfy the diverse customer demands. The meal delivery routing problem is addressed with an order allocation strategy based on transfer stations through developing a three-stage modelling framework consisting of order combination, splitting and delivery routing for the online-to-offline instant logistics services. Normal meal orders are combined by the DBSCAN algorithm, and the cross-regional long-distance orders are split by transfer stations. Based on order combination and splitting, a mixed integer programming model is constructed for the meal delivery routing problem and solved by the adaptive large neighbourhood search algorithm. The proposed algorithm converges quickly for the tested instances constructed based on real platform data. The proposed order allocation strategy can expand the delivery scopes of couriers effectively, stimulate more potential orders and guarantee the timeliness of meal delivery.