We consider the problem of designing lightweight load-bearing frame structures with additive manufacturability constraints. Specifically, we focus on mathematical programming approaches to finding exact globally optim...
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We consider the problem of designing lightweight load-bearing frame structures with additive manufacturability constraints. Specifically, we focus on mathematical programming approaches to finding exact globally optimal solutions, given a pre-specified discrete ground structure and continuous design element dimensions. We take advantage of stiffness matrix decomposition techniques and expand on some of the existing modeling approaches, including exact mixed-integer nonlinear programming and its mixed-integer linear programming restrictions. We propose a (non-convex) quadratic formulation using semi-continuous variables, motivated by recent progress in state-of-the-art quadratic solvers, and demonstrate how some additive-specific restrictions can be incorporated into mathematical optimization. While we show with numerical experiments that the proposed methods significantly reduce the required solution time for finding global optima compared to other formulations, we also observe that even with these new techniques and advanced computational resources, discrete modeling of frame structures remains a tremendously challenging problem.
A vehicle scheduling problem (VSP) that arises from sugar beet transportation within minimum working time under the set of constraints reflecting a real-life situation is considered. A mixedintegerquadratically cons...
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A vehicle scheduling problem (VSP) that arises from sugar beet transportation within minimum working time under the set of constraints reflecting a real-life situation is considered. A mixed integer quadratically constrained programming (MIQCP) model of the considered VSP and reformulation to a mixedinteger linear program (MILP) are proposed and used within the framework of Lingo 17 solver, producing optimal solutions only for small-sized problem instances. Two variants of the variable neighborhood search (VNS) metaheuristic-basic VNS (BVNS) and skewed VNS (SVNS) are designed to efficiently deal with large-sized problem instances. The proposed VNS approaches are evaluated and compared against Lingo 17 and each other on the set of real-life and generated problem instances. Computational results show that both BVNS and SVNS reach all known optimal solutions on small-sized instances and are comparable on medium- and large-sized instances. In general, SVNS significantly outperforms BVNS in terms of running times.
Travel time in urban centers is a significant contributor to the quality of living of its citizens. Mobility on Demand (MoD) services such as Uber and Lyft have revolutionized the transportation infrastructure, enabli...
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Travel time in urban centers is a significant contributor to the quality of living of its citizens. Mobility on Demand (MoD) services such as Uber and Lyft have revolutionized the transportation infrastructure, enabling new solutions for passengers. Shared MoD services have shown that a continuum of solutions can be provided between the traditional private transport for an individual and the public mass transit-based transport, by making use of the underlying cyber-physical substrate that provides advanced, distributed, and networked computational and communicational support. In this article, we propose a novel shared mobility service using a dynamic framework. This framework generates a dynamic route for multi-passenger transport, optimized to reduce time costs for both the shuttle and the passengers and is designed using a new concept of a space window. This concept introduces a degree of freedom that helps reduce the cost of the system involved in designing the optimal route. A specific algorithm based on the Alternating Minimization approach is proposed. Its analytical properties are characterized. Detailed computational experiments are carried out to demonstrate the advantages of the proposed approach and are shown to result in an order of magnitude improvement in the computational efficiency with minimal optimality gap when compared to a standard mixed integer quadratically constrained programming-based algorithm.
A novel energy management model for connected co-phase traction power system (CCTPS) is proposed, in which hybrid energy storage systems (HESS) and photovoltaic (PV) are considered, and the power exchanges between adj...
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ISBN:
(纸本)9781538694909
A novel energy management model for connected co-phase traction power system (CCTPS) is proposed, in which hybrid energy storage systems (HESS) and photovoltaic (PV) are considered, and the power exchanges between adjacent traction substations (TSSs) can be fulfilled via power transfer controller (PTC). The energy management strategy aims at coordinating the regenerative braking energy, local renewable energy and the peak-valley difference between adjacent TSSs so as to minimize the daily operating costs of CCTPS, and the three phase voltage unbalance constraints are particularly considered, which is a remarkable contribution of this study. This optimization problem is formulated as a mixed integer quadratically constrained programming (MIQCP) model and solved by CPLEX solver. The proposed strategy. is tested with a real high-speed railway line and two cases are analyzed and compared. The simulation results show that the developed energy management of CCTPS brings about significant economic benefits while the three-phase voltage unbalance is in line with national standards.
Low price of raw materials in sugar industry and characteristics of production method lead to the specific transport organization problem. A new variant of Vehicle Scheduling Problem (VSP) that arises from transportat...
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