An exact approach for the grocery delivery problem in urban areas

In this paper, we face the problem of delivering a given amount of goods in urban areas in a business-to-consumer (B2C) electronic commerce (EC) environment. This problem can be considered as a particular case of vehicle routing problem. As a novel issue, here we have to determine the fleet of no homogeneous vehicles to be used for satisfying the demands of clients coming from grocery e-channels, and their related itineraries, given the traveling limits imposed by the urban government; in fact, commercial vehicles are not allowed to go everywhere and can travel only in restricted daily time windows, according to their pollution emissions. We have to minimize the overall distribution costs, taking into account traveling components and setup ones, together with operative aspects and environmental issues; customer requirements, vehicle capacity and daily shift constraints have to be satisfied too. We outline the main characteristics of the problem in a B2C EC environment and propose a mixed integer linear programming model to solve this NP-hard problem. Computational results of test bed cases related to different sized transportation networks and delivery demands are presented and analyzed with respect to the fleet of vehicles chosen for satisfying the customer demand and the street traffic limitations. Then, a realistic case study derived from the e-distribution channel of a grocery company of Genoa, Italy, is reported. Considerations about CPU time and optimality gap are also given with the idea of making the proposed model effectively used and solved with any commercial software

Analytical Modeling Framework to Assess the Economic and Environmental Impacts of Residential Deliveries, and Evaluate Sustainable Last-Mile Strategies

In the last decade, e‐commerce has grown substantially, increasing business‐to‐business, business‐to‐consumer, and consumer‐to‐consumer transactions. While this has brought prosperity for the e-retailers, the ever-increasing consumer demand has brought more trucks to the residential areas, bringing along externalities such as congestion, air and noise pollution, and energy consumption. To cope with this, different logistics strategies such as the introduction of micro-hubs, alternative delivery points, and use of cargo bikes and zero emission vehicles for the last mile have been introduced and, in some cases, implemented as well. This project, hence, aims to develop an analytical framework to model urban last mile delivery. In particular, this study will build upon the previously developed econometric behavior models that capture e-commerce demand. Then, based on continuous approximation techniques, the authors will model the last-mile delivery operations. And finally, using the cost-based sustainability assessment model (developed in this study), the authors will estimate the economic and environmental impacts of residential deliveries under different city logistics strategies.View the NCST Project Webpag

Collaboration in urban distribution of online grocery orders

Purpose: Population growth, urbanisation and the increased use of online shopping are some of the key challenges affecting the traditional logistics model. The purpose of this paper is to focus on the distribution of grocery products ordered online and the subsequent home delivery and click and collect services offered by online retailers to fulfil these orders. These services are unsustainable due to increased operational costs, carbon emissions, traffic and noise. The main objective of the research is to propose sustainable logistics models to reduce economic, environmental and social costs whilst maintaining service levels. Design/methodology/approach: The authors have a mixed methodology based on simulation and mathematical modelling to evaluate the proposed shared logistics model using: primary data from a major UK retailer, secondary data from online retailers and primary data from a consumer survey on preferences for receiving groceries purchased online. Integration of these three data sets serves as input to vehicle routing models that reveal the benefits from collaboration by solving individual distribution problems of two retailers first, followed by the joint distribution problem under single decision maker assumption. Findings: The benefits from collaboration could be more than 10 per cent in the distance travelled and 16 per cent in the time required to deliver the orders when two online grocery retailers collaborate in distribution activities. Originality/value: The collaborative model developed for the online grocery market incentivises retailers to switch from current unsustainable logistics models to the proposed collaborative models

Integrating sensors data in optimization methods for sustainable urban logistic

L'abstract è presente nell'allegato / the abstract is in the attachmen

The future of grocery stores : Omnichannel and AI technologies and Next-Generation Brick-and-Mortar Grocery Stores

In recent years the grocery retail industry has been experiencing tremendous change, driven mainly by advances in technology. Traditional brick-and-mortar grocery stores are under threat from industry disruptors who incorporate new technologies into their business models and operate with online channels. Therefore, this paper introduces omnichannel and artificial intelligence (AI) use cases as factors influencing the future success of brick-and-mortar grocery stores. To identify critical drivers for success, semi-structured expert interviews were conducted to discover how grocers can implement an omnichannel strategy and combine various AI technologies to remain competitive. Furthermore, a customer survey tested the acceptance of specific use cases and scrutinized the resulting increase or decrease in shopping frequency due to omnichannel in conjunction with AI. The analysis indicates an upcoming change in the grocery industry. A move towards a combination of an online and offline world is rising. Moreover, use cases like online shopping, personalized prices and offers, and cashier-free checkouts have the highest potential to increase the points-of-delight by consumers while grocery shopping. Therefore, grocers must adopt an omnichannel strategy and incorporate several AI-driven technologies to increase profits and remain competitive.Nos últimos anos, a indústria retalhista de mercearia tem vindo a sofrer mudanças tremendas, impulsionadas principalmente pelos avanços da tecnologia. As mercearias tradicionais de tijolo e cimento estão ameaçadas pelos disruptores da indústria que incorporam novas tecnologias nos seus modelos de negócio e operam com canais em linha. Por conseguinte, este documento introduz casos de uso omnichannel e de inteligência social (AI) como factores que influenciam o sucesso futuro das mercearias de tijolo e de marfim. Para identificar factores críticos para o sucesso, foram realizadas entrevistas semi-estruturadas com peritos para descobrir como os merceeiros podem implementar uma estratégia de omnichannel e com-bine várias tecnologias de AI para se manterem competitivos. Além disso, um inquérito aos clientes testou a aceitação de casos específicos de uso e examinou o aumento ou diminuição da frequência de compras resultante devido ao omnichannel em conjunto com a AI. A análise indica uma próxima mudança na indústria de mercearia. Está a aumentar uma tendência para uma combinação de um mundo online e offline. Além disso, casos de utilização como as compras online, preços e ofertas personalizadas, e caixas sem caixa têm o potencial mais elevado para aumentar os pontos de venda dos consumidores enquanto fazem compras de mercearia. Por conseguinte, os merceeiros devem adoptar uma estratégia omnichannel e incorporar várias tecnologias impulsionadas pela AI para aumentar os lucros e permanecer competitivos

Contributions to sustainable urban transport : decision support for alternative mobility and logistics concepts

Increasing transport activities in cities are a substantial driver for congestion and pollution, influencing urban populations’ health and quality of life. These effects are consequences of ongoing urbanization in combination with rising individual demand for mobility, goods, and services. With the goal of increased environmental sustainability in urban areas, city authorities and politics aim for reduced traffic and minimized transport emissions. To support more efficient and sustainable urban transport, this cumulative dissertation focuses on alternative transport concepts. For this purpose, scientific methods and models of the interdisciplinary information systems domain combined with elements of operations research, transportation, and logistics are developed and investigated in multiple research contributions. Different transport concepts are examined in terms of optimization and acceptance to provide decision support for relevant stakeholders. In more detail, the overarching topic of urban transport in this dissertation is divided into the complexes urban mobility (part A) in terms of passenger transport and urban logistics (part B) with a focus on the delivery of goods and services. Within part A, approaches to carsharing optimization are presented at various planning levels. Furthermore, the user acceptance of ridepooling is investigated. Part B outlines several optimization models for alternative urban parcel and e-grocery delivery concepts by proposing different network structures and transport vehicles. Conducted surveys on intentional use of urban logistics concepts give valuable hints to providers and decision makers. The introduced approaches with their corresponding results provide target-oriented support to facilitate decision making based on quantitative data. Due to the continuous growth of urban transport, the relevance of decision support in this regard, but also the understanding of the key drivers for people to use certain services will further increase in the future. By providing decision support for urban mobility as well as urban logistics concepts, this dissertation contributes to enhanced economic, social, and environmental sustainability in urban areas