13 research outputs found

    Analysis of a Parallel Machine Scheduling Problem with Sequence Dependent Setup Times and Job Availability Intervals

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    In this study, we propose constraint programming (CP) model and logic-based Benders algorithms in order to make the best decisions for scheduling non-identical jobs with availability intervals and sequence dependent setup times on unrelated parallel machines in a fixed planning horizon. In this problem, each job has a profit, cost and must be assigned to at most one machine in such a way that total profit is maximized. In addition, the total cost has to be less than or equal to a budget level. Computational tests are performed on a real-life case study prepared in collaboration with the U.S. Army Corps of Engineers (USACE). Our initial investigations show that the pure CP model is very efficient in obtaining good quality feasible solutions but, fails to report the optimal solution for the majority of the problem instances. On the other hand, the two logic-based Benders decomposition algorithms are able to obtain near optimal solutions for 86 instances out of 90 examinees. For the remaining instances, they provide a feasible solution. Further investigations show the high quality of the solutions obtained by the pure CP model

    Optimal Dredge Fleet Scheduling Within Environmental Work Windows

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    The U. S. Army Corps of Engineers oversees dredging in hundreds of navigation projects annually, through its fleet of government equipment and through individual contracts with private industry. The research presented here sought to examine the decision to allocate dredge resources to projects systemwide under necessary constraints. These constraints included environmental restrictions on when dredging could take place in response to the migration patterns of turtles, birds, fish, and other wildlife; dredge equipment resource availability; and varying equipment productivity rates that affected project completion times. The paper discusses problem definition and model formulation of optimal dredge fleet scheduling within environmental work windows. In addition, a sensitivity analysis was conducted to provide decision makers with quantitative insights into dredging program efficiency gains that could be realized systemwide if environmental restrictions were relaxed. Opportunities exist to provide decision makers with quantitative insights into how efficiencies might be obtained if targeted research were to show that particular restricted periods could be relaxed without adverse consequences to sensitive and endangered species

    Economic Impact of Investment Scenarios in the McClellan-Kerr Arkansas River Navigation System

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    The McClellan–Kerr Arkansas River Navigation System (MKARNS) is challenged by an aging infrastructure and by limited maintenance budgets, all of which cause transportation delays. In this study, the Maritime Transportation Simulator (MarTranS), which is a hybrid of agent-based modeling, discrete-event simulation, system dynamics, and multiregional input-output analysis, was adopted to model the relationship between the components of the system and economic impact factors. Real-world scenarios were analyzed to explore the economic impacts of various patterns of investment in the MKARNS. These scenarios include a base scenario (in which the system infrastructure remains unchanged and no future investments are made), investment scenarios (e.g., investing in deepening of the navigation channel, port expansion, and lock/dam rehabilitation), and a demand-change scenario focused on the impacts of the Panama Canal expansion. The results reveal that the MKARNS under current circumstances is not sustainable in the long term and that future economic investment is needed if it is to continue operations. In addition, among the different system components, locks/dams are the primary sources of system delays, so these should be targeted for investment and reconstruction to sustain and enhance the beneficial economic impacts of the system

    A Review of System Dynamics in Maritime Transportation

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    Towards the end of the twentieth century, a number of factors have re-shaped the shipping industry including the growth of international trade, the emergence of new markets, and the development of multimodal supply chains. The maritime transportation system consists of ocean and coastal routes, inland waterways, railways, roads, and air freight and is a vital part of the global supply chain and freight transportation system. Due to the complexity of the maritime transportation system (MTS), multiple transportation systems interconnect to achieve a purpose. We have identified system dynamics (SD) as an appropriate approach to study the MTS and its integration with multimodal transportation. In the initial phase of this research, we conducted a literature review of SD applications in the MTS. The result of our literature review provides an overview of SD modeling in the MTS and generates future research questions in this area
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