INTEGRATED HUB LOCATION AND CAPACITATED VEHICLE ROUTING PROBLEM OVER INCOMPLETE HUB NETWORKS

Hub location problem is one of the most important topics encountered in transportation and logistics management. Along with the question of where to position hub facilities, how routes are determined is a further challenging problem. Although these two problems are often considered separately in the literature, here, in this study, the two are analyzed together. Firstly, we relax the restriction that a vehicle serves between each demand center and hub pair and propose a mixed-integer mathematical model for the single allocation p-hub median and capacitated vehicle routing problem with simultaneous pick-up and delivery. Moreover, while many studies in hub location problem literature assume that there is a complete hub network structure, we also relax this assumption and present the aforementioned model over incomplete hub networks. Computational analyses of the proposed models were conducted on various instances on the Turkish network. Results indicate that the different capacity levels of vehicles have an important impact on optimal hub locations, hub arc networks, and routing design

Fostering collaboration and coordination in urban delivery: a multi-agent microsimulation model

Given the dynamic nature of Urban Freight Transport (UFT) processes, the involved transport and logistics operators face with internal and external issues that should tackle to improve last-mile levels of service and decrease total costs while performing delivery operations. Customers (i.e., freight receivers) perceive the level of service through the acceptance of their requests, while total operational costs are mainly determined by the total travel costs (i.e., distance and/or time) required to accomplish the customers' request. In addition, the vehicle-kilometres travelled are related to the externalities produced. Given that the actors involved in the process operate in a stochastic environment (with changes that can occur both in terms of demand – receivers' requests, and in supply – travel times), collaboration and coordination among the operators could play a key role in meeting the customers' requests as well as in reducing both internal and external delivery costs. Therefore, the paper proposes an UFT modelling framework that integrates collaboration and coordination processes among the different involved actors, and allows the benefits to be assessed. The model has a multi-agent architecture based on microsimulation. In particular, the multi-agent architecture allows us to point out the different actors’ responses to various internal (e.g., delivery requests) and external (e.g., delivery times) changes occurring in the daily delivery operations. It consists of three layers. The first one simulates the interactions among actors operating collaboratively. The second layer microsimulates the collaborative processes of information management. Finally, a third layer integrates the two previous layers, facilitating a decision-making process in such a dynamic context. The whole modelling framework is tested in a real case study in which it is possible to validate pros and cons of working in a collaborative and coordinative environment. The results show significant benefits from actors/operators involved in the process and subsequently can address the policy/measure implementation towards a more sustainable and liveable city

Enriching the tactical network design of express service carriers with fleet scheduling characteristics

Express service carriers provide time-guaranteed deliveries of parcels via a network consisting of nodes and hubs. In this, nodes take care of the collection and delivery of parcels, and hubs have the function to consolidate parcels in between the nodes. The tactical network design problem assigns nodes to hubs, determines arcs between hubs, and routes parcels through the network. Afterwards, fleet scheduling creates a schedule for vehicles operated in the network. The strong relation between flow routing and fleet scheduling makes it difficult to optimise the network cost. Due to this complexity, fleet scheduling and network design are usually decoupled. We propose a new tactical network design model that is able to include fleet scheduling characteristics (like vehicle capacities, vehicle balancing, and drivers' legislations) in the network design. The model is tested on benchmark data based on instances from an express provider, resulting in significant cost reductions

Modeling the Impact of Technological Changes on Urban Commercial Trips by Commercial Activity Routing Type

An array of noteworthy developments in logistics practice has taken place without an equivalent and comprehensive development in urban freight transportation modeling. Part of the problem is the lack of deep understanding of the workings of distribution processes in relation to the generation of truck traffic. In this paper it is emphasized the role and importance that distribution network size, and information and communication technology have on the truck traffic flows that materializes as the supply chain that flows over the public infrastructure. This paper develops the concept of commercial activity routing types that characterize the interplay between transportation demand requests and routing characteristics. This research contributes to the field proposing a novel and detailed characterization of truck flows in a supply chain context. Using well-known yet simple models and formulas from vehicle routing, operations research, and management science literature, we derive behavioral insights about distributors and carriers’ routing and order sizing decisions, as routing constraints and second order effects are important drivers of truck flows. The main contribution is to bring a new commercial activity-routing perspective and deeper level of operational decision-making analysis to cope with the intricacies of freight transportation modeling

Commercial Helicopter Services: Toward Quantitative Solutions for Understanding Industry Phenomena and Achieving Stakeholder Optimization

An understanding of industry phenomena and optimization techniques within the upstream energy industry’s transportation sector is markedly absent in the extant literature and suitable for rigorous investigation. This manuscript presents analyses related to the optimization of offshore worker transportation and econometric analyses of factors influencing commercial helicopter operators’ stock returns, which are represented throughout the manuscript as Part I and Part II, respectively. The global energy industry transports supplies and personnel via helicopter to offshore locations and has been increasingly focusing on optimizing upstream logistics. Using a unique sample of deepwater and ultra-deepwater permanent offshore locations in the Gulf of Mexico, transportation networks consisting of 58 locations operated by 19 firms are optimized via a randomized greedy algorithm. The model developed in Part I has been found to effectively solve the complex transportation problem and simulation results show the potential advantages of alternative clustered and integrated network structures, as compared to an independent firm-level structure. The evaluation of clustered and integrated network structures, which allow ride sharing via energy firm cooperation, provides evidence that such network structures may yield cost reductions for participating firms. The extent to which commercial helicopter operators’ stock returns are related to commodity prices and other relevant industry variables is absent in the extant literature. Often, firms attribute favorable results to internal factors whereas unfavorable results are attributed to external factors. Using a unique data set from 2013-2018, the current research identifies structural relationships between crude oil prices, natural gas prices, the rotary rig count, a subset of the overall market, firms’ degree of diversification and stock returns of commercial helicopter operators. Empirical analyses developed in Part II show that the prevalent price of crude oil and the overall market environment possess explanatory power of commercial helicopter firms’ stock returns, ceteris paribus. Specifically, 10% increases in the crude oil price and the S&P 500 index yield a 2.7% and 8.0% increase in stock returns, respectively. Collectively, the abovementioned parts of this manuscript provide rigorous, quantitative analyses of topics unrepresented within the extant literature, which are foundational for future practice and research. Specifically, new knowledge regarding a practical approach to model development and solution deliverance for the transportation of offshore workers to their respective locations and factors influencing commercial helicopter operators’ stock returns has been appropriately designed and empirically evaluated