1,041 research outputs found
Proactive model to determine information technologies supporting expansion of air cargo network
Shippers and recipients expect transportation companies to provide more than just the movement of a package between points; certain information must be available to them as well, to enable forecasts and plans within the supply chain.
The transportation companies also need the information flow that undergirds a transportation grid, to support ad-hoc routing and strategic structural re-alignment of business processes.
This research delineates the information needs for an expanding air cargo network, then develops a new model of the information technologies needed to support expansion into a new country. The captured information will be used by shippers, recipients, and the transportation provider to better guide business decisions. This model will provide a method for transportation companies to balance the tradeoffs between the operating efficiencies, capital expenditures, and customer expectations of their IT systems. The output of the model is a list of technologies â optimized by cost â which meet the specific needs of internal and external customers when expanding air cargo networks into a new country
Supply chain management: An opportunity for metaheuristics
In todayâs highly competitive and global marketplace the pressure on organizations to find new ways to create and deliver value to customers grows ever stronger. In the last two decades, logistics and supply chain has moved to the center stage. There has been a growing recognition that it is through an effective management of the logistics function and the supply chain that the goal of cost reduction and service enhancement can be achieved. The key to success in Supply Chain Management (SCM) require heavy emphasis on integration of activities, cooperation, coordination and information sharing throughout the entire supply chain, from suppliers to customers. To be able to respond to the challenge of integration there is the need of sophisticated decision support systems based on powerful mathematical models and solution techniques, together with the advances in information and communication technologies. The industry and the academia have become increasingly interested in SCM to be able to respond to the problems and issues posed by the changes in the logistics and supply chain. We present a brief discussion on the important issues in SCM. We then argue that metaheuristics can play an important role in solving complex supply chain related problems derived by the importance of designing and managing the entire supply chain as a single entity. We will focus specially on the Iterated Local Search, Tabu Search and Scatter Search as the ones, but not limited to, with great potential to be used on solving the SCM related problems. We will present briefly some successful applications.Supply chain management, metaheuristics, iterated local search, tabu search and scatter search
Mixing quantitative and qualitative methods for sustainable transportation in Smart Cities
L'abstract è presente nell'allegato / the abstract is in the attachmen
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Centralized versus market-based approaches to mobile task allocation problem: State-of-the-art
Centralized approach has been adopted for finding solutions to resource allocation problems (RAPs) in many real-life applications. On the other hand, market-based approach has been proposed as an alternative to solve the problem due to recent advancement in ICT technologies. In spite of the existence of some efforts to review the pros and cons of each approach in RAPs, the studies cannot be directly applied to specific problem domains like mobile task allocation problem which is characterised with high level of uncertainty on the availability of resources (workers). This paper aims to review existing studies on task allocation problems(TAPs) focusing on those two approaches and their comparison and identify major issues that need to be resolved for comparing the two approaches in mobile task allocation problems. Mobile Task Allocation Problem (MTAP) is defined and its problematic structures are explained in relation with task allocation to mobile workers. Solutions produced by each approach to some applications and variations of MTAP are also discussed and compared. Finally, some future research directions are identified in order to compare both approaches in function of uncertainty emerging from the mobile nature of the MTAP
Last-mile logistics optimization in the on-demand economy
L'abstract è presente nell'allegato / the abstract is in the attachmen
Dynamic vehicle routing problems: Three decades and counting
Since the late 70s, much research activity has taken place on the class of dynamic vehicle routing problems (DVRP), with the time period after year 2000 witnessing a real explosion in related papers. Our paper sheds more light into work in this area over more than 3 decades by developing a taxonomy of DVRP papers according to 11 criteria. These are (1) type of problem, (2) logistical context, (3) transportation mode, (4) objective function, (5) fleet size, (6) time constraints, (7) vehicle capacity constraints, (8) the ability to reject customers, (9) the nature of the dynamic element, (10) the nature of the stochasticity (if any), and (11) the solution method. We comment on technological vis-à -vis methodological advances for this class of problems and suggest directions for further research. The latter include alternative objective functions, vehicle speed as decision variable, more explicit linkages of methodology to technological advances and analysis of worst case or average case performance of heuristics.Š 2015 Wiley Periodicals, Inc
Analytical model for large-scale design of sidewalk delivery robot systems
With the rise in demand for local deliveries and e-commerce, robotic
deliveries are being considered as efficient and sustainable solutions.
However, the deployment of such systems can be highly complex due to numerous
factors involving stochastic demand, stochastic charging and maintenance needs,
complex routing, etc. We propose a model that uses continuous approximation
methods for evaluating service trade-offs that consider the unique
characteristics of large-scale sidewalk delivery robot systems used to serve
online food deliveries. The model captures both the initial cost and the
operation cost of the delivery system and evaluates the impact of constraints
and operation strategies on the deployment. By minimizing the system cost,
variables related to the system design can be determined. First, the
minimization problem is formulated based on a homogeneous area, and the optimal
system cost can be derived as a closed-form expression. By evaluating the
expression, relationships between variables and the system cost can be directly
obtained. We then apply the model in neighborhoods in New York City to evaluate
the cost of deploying the sidewalk delivery robot system in a real-world
scenario. The results shed light on the potential of deploying such a system in
the future
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