Search results

Production and transportation of precast components, as two continuous service stages of a precast plant, play an important role in meeting customer needs and controlling costs. However, there is still a lack of production and transportation scheduling methods that comprehensively consider delivery timeliness and transportation economy. This article aims to study the integrated scheduling optimization problem of in-plant flowshop production and off-plant transportation under the consideration of practical constraints of customer order delivery time window, and seek an optimal scheduling method that balances delivery timeliness and transportation economy.

In this study, an integrated scheduling optimization model of flowshop production and transportation for precast components with delivery time windows is established, which describes the relationship between production and transportation and handles transportation constraints under the premise of balancing delivery timeliness and transportation economy. Then a genetic algorithm is designed to solve this model. It realizes the integrated scheduling of production and transportation through double-layer chromosome coding. A program is designed to realize the solution process. Finally, the validity of the model is proved by the calculation of actual enterprise data.

The optimized scheduling scheme can not only meet the on-time delivery, but also improve the truck loading rate and reduce the total cost, composed of early cost in plant, delivery penalty cost and transportation cost. In the model validation, the optimal scheduling scheme uses one less truck than the traditional EDD scheme (saving 20% of the transportation cost), and the total cost can be saved by 17.22%.

This study clarifies the relationship between the production and transportation of precast components and establishes the integrated scheduling optimization model and its solution algorithm. Different from previous studies, the proposed optimization model can balance the timeliness and economy of production and transportation for precast components.

The purpose of this paper is to investigate the impact of risk on the project delivery selection process of three primary methods in use in the USA, including design-bid-build (DBB); design-build (DB); and construction manager/general contractor (CMGC).

The review of empirical studies, national survey questionnaire, multivariate analysis, and cross-validating discussion are adopted for this research. The risk factors were identified through an exhaustive literature review and empirical studies that included more than $10 billion of transportation projects. Experts with an average of 25 years of professional experience related to risk and project delivery methods in the transportation industry were invited to participate in the survey.

There were six critical risk factors for DBB, seven for DB, and six for CMGC. These critical risk factors are ranked differently from each delivery method. The most critical risk factor for DBB is construction risk, for DB is scope risk, and for CMGC is constructability and documentation risk.

Knowledge of the risk factors will allow researchers to better understand the impact of risk on DBB, DB, and CMGC projects. The chief limitation of this research is that the primary data were mostly opinions from experts although several empirical data were collected for cross-validation. The future research may take into account the role of participant's risk aversion in project delivery decision frameworks.

Transportation agencies and other practitioners can use these risk factors to make more effective and defensible decisions on which delivery method is the most suitable for their projects. The result from this study provides a foundation for decision makers to use a risk-based approach in the project delivery decision.

This research is the first attempt to examine the impact of risk on the project delivery selection process.

The development of e-grocery allows people to purchase food online and benefit from home delivery service. Nevertheless, a high rate of failed deliveries due to the customer’s absence causes significant loss of logistics efficiency, especially for perishable food. The purpose of this paper is to propose an innovative approach to use customer-related data to optimize e-grocery home delivery. The approach estimates the absence probability of a customer by mining electricity consumption data, in order to improve the success rate of delivery and optimize transportation.

The methodological approach consists of two stages: a data mining stage that estimates absence probabilities, and an optimization stage to optimize transportation.

Computational experiments reveal that the proposed approach could reduce the total travel distance by 3-20 percent, and theoretically increase the success rate of first-round delivery approximately by18-26 percent.

The proposed approach combines two attractive research streams on data mining and transportation planning to provide a solution for e-commerce logistics.

This study gives an insight to e-grocery retailers and carriers on how to use customer-related data to improve home delivery effectiveness and efficiency.

The proposed approach can be used to reduce environmental footprint generated by freight distribution in a city, and to improve customers’ experience on online shopping.

Being an experimental study, this work demonstrates the effectiveness of data-driven innovative solutions to e-grocery home delivery problem. The paper also provides a methodological approach to this line of research.

The advent of grocery sales through online channels necessitates that bricks-and-mortar retailers redefine their logistics networks if they want to compete online. Because the general understanding of such bricks-and-clicks logistics systems for grocery is still limited, the purpose of this paper is to analyze the internal logistics networks used to serve customers across channels by means of an exploratory study with retailers from different contexts.

A total of 12 case companies from six European countries participated in this exploratory study. Face-to-face interviews with managers were the primary source for data collection. The heterogeneity of the sample enabled the authors to build a typology of logistics networks in grocery retailing on multiple channels and to understand the advantages of different warehousing, picking, internal transportation and last-mile delivery systems.

Bricks-and-mortar grocery retailers are leveraging their existing logistics structures to fulfill online orders. Logistics networks are mostly determined by the question of where to split case packs into customer units. In non-food logistics, channel integration is mostly seen as beneficial, but in grocery retailing, this depends heavily on product, market and retailer specifics. The data from the heterogeneous sample reveal six distinct types for cross-channel order fulfillment.

The qualitative analysis of different design options can serve as a decision support for retailers developing logistics networks to serve customers across channels.

The paper shows the internal and external factors that drive the decision-making for omni-channel (OC) logistics networks for previously store-based grocery retailers. Thereby, it makes a step toward building a contingency and configuration theory of retail networks design. It discusses in particular the differences between grocery and non-food OC retailing, last-mile delivery systems and market characteristics in the decision-making of retail networks design.

The purpose of this paper is to generate a performance model for an order‐to‐delivery (OTD) process in delivery scheduling environments. It aims to do this with a triadic approach, encompassing a customer, a supplier and a logistics service provider.

The paper takes the form of a conceptual analysis and a triadic case study on performance measurement requirements in an OTD process characterized by delivery scheduling, and generating performance models.

Two OTD process performance models, one for the supplier's delivery sub‐process and one for the customer's delivery scheduling, the logistics service provider's transportation and the customer's good receipt sub‐process, in delivery scheduling environments are generated.

A single case study limits the levels of external validity and reliability to analytical generalization.

The generated performance models include definitions of four sub‐processes and outline ten performance dimensions that should be of relevance for several companies to apply.

This is the first approach that generates performance models for a triadic OTD process for use in delivery scheduling environments.

After the occurrence of natural disasters, the rapid and accurate delivery of geo-afforestation is the key to emergency rescue and is the fundamental solution to the “last mile” problem. It provides technical support for the territorial rapid and accurate delivery. The paper aims to discuss this issue.

Through literature and theoretical research, combined with the research experience of scholars, the qualitative research method is adopted. The paper establishes a three-dimensional analysis framework, including disaster predictability, resource availability and transport accessibility, and proposes the integrated delivery triangular technical framework, including integrated monitoring analysis, the territorial virtual public storage and transportation.

Based on the analysis of the factors affecting the effectiveness of emergency delivery, the paper establishes a three-dimensional analysis framework, including disaster predictability, resource availability and transport accessibility, and proposes the integrated delivery triangular technical framework, including integrated monitoring analysis, the territorial virtual public storage and transportation. The triangular technical characteristics and functions of emergency delivery are studied, providing theoretical basis and technical support for effective rescue and emergency planning.

The territorial emergency delivery refers to the process of rapid and accurate delivery without relying on external territorial supplies. The paper establishes a three-dimensional analysis framework, including disaster predictability, resource availability and transport accessibility, and proposes the integrated delivery triangular technical framework, including integrated monitoring analysis, the territorial virtual public storage and transportation.

This study aims to minimize the cost and time of blood delivery in the whole blood supply chain network (BSCN) in disaster conditions. In other words, integrating all strategic, tactical and operational decisions of three levels of blood collection, processing and distribution leads to satisfying the demand at the right time.

This paper proposes an integrated BSCN in disaster conditions to consider four categories of facilities, including temporary blood collection centers, field hospitals, main blood processing centers and medical centers, to optimize demand response time appropriately. The proposed model applies the location of all permanent and emergency facilities in three levels: blood collection, processing and distribution. Other essential decisions, including multipurpose facilities, emergency transportation, inventory and allocation, were also used in the model. The LP metric method is applied to solve the proposed bi-objective mathematical model for the BSCN.

The findings show that this model clarifies its efficiency in the total cost and blood delivery time reduction, which results in a low carbon transmission of the blood supply chain.

The researchers proposed an integrated BSCN in disaster conditions to minimize the cost and time of blood delivery. They considered multipurpose capabilities for facilities (e.g. field hospitals are responsible for the three purposes of blood collection, processing and distribution), and so locating permanent and emergency facilities at three levels of blood collection, processing and distribution, support facilities, emergency transportation and traffic on the route with pollution were used to present a new model.

The purpose of this paper is to introduce a three-echelon multimodal transportation problem applied to a humanitarian logistic case study that occurred in Mexico.

This study develops a methodology combining a transshipment problem and an adaptation of the multidepot heterogeneous fleet vehicle routing problem to construct a mathematical model that incorporates the use of land-based vehicles and drones. The model was applied to the case study of the Earthquake on September 19, 2017, in Mexico, using the Gurobi optimization solver.

The results ratified the relevance of the study, showing an inverse relationship between transportation costs and delivery time; on the flip side, the model performed in a shorter CPU time with medium and small instances than with large instances.

While the size of the instances limits the use of the model for big-scale problems, this approach manages to provide a good representation of a transportation network during a natural disaster using drones in the last-mile deliveries.

The present study contributes to a model that combines a vehicle routing problem with transshipment, multiple depots and a heterogeneous fleet including land-based vehicles and drones. There are multiple models present in the literature for these types of problems that incorporate the use of these transportation modes; however, to the best of the authors’ knowledge, there are still no proposals similar to this study.

With the increasing urbanization rates in emerging countries such as the ones in Latin America and the Caribbean, urban logistics solutions and initiatives are widely needed. Urban planners often consider only passenger transportation and leave freight transportation unattended, thus increasing externalities and degrading the transportation of goods. This chapter presents three urban logistics solutions, which intend to tackle problems related to urbanization and last mile delivery operations challenges by evaluating location models for loading and unloading bays, urban transfer centers location models, and freight trip generation models. The presented solutions were proposed by several researchers of the Institute of Innovation in Productivity and Logistics CATENA-USFQ over the last four years and remain theoretical at the moment. However, we present estimated results of potential implementations in three districts of Quito: Historic Center, Entertainment District, and Corporate District. This chapter not only presents the mentioned urban logistics solutions in Quito but also gives an overview of the followed methodology, which can be replicated in countries and cities of similar characteristics of the region.

This research investigates procedures and effective practices on staffing needs and utilization for successful implementation of alternative contracting methods (ACMs) in the United Sates, including design–build (D–B) and construction manager/general contractor (CM/GC) delivery methods.

The review of published empirical studies, a national survey of transportation agencies and case studies of highway agencies form the basis of the conclusions in this research. In addition to the national survey, with 46 of 50 agencies participating, the research presents case studies from five highway agencies in the United States including the following: California, Florida, Georgia, Minnesota and Virginia. These five case studies were selected from agencies that have extensive experience in delivering ACM projects. The case studies involved a thorough procedural review and structured interviews of agency personnel. The agencies then validated the results and conclusions.

The results showed that implementing ACM projects requires different knowledge, skills and management and coordination efforts than traditional design–bid–build (D–B–B) projects. The study found that the key success factors of implementing ACMs are the following: (1) establishment of an ACM champion; (2) active involvement of key staff throughout the ACM project development process; (3) appropriate use of consultants and (4) ACM training and staff development.

The issue on how to attract and retain talented staff and a committed core workforce with appropriate skills and competences for ACM implementation is vital for highway agencies, but it lacks information and guidance. The chief limitation of this research is that the primary data were collected from highway agencies in the United Sates. Any future research should include more data to enhance the validity of this study outside of the public transportation sector.

Developing a sustainable level of core staff plays an important role in implementing an ACM program. The result of this research will help transportation agencies and other public owners to develop effective staffing strategies for successful implementation of ACMs. The findings of this research also address the appropriate use of consultants to supplement core staff with regard to delivery of ACM projects.

This research is the first attempt to examine the staffing needs and utilization for ACM projects.