In many densely populated mega -cities around the world, metro systems are becoming overly saturated by the ever-increasing travel demand, which results in overcrowded stations, excessive delay, and unsafe anxieties a...
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In many densely populated mega -cities around the world, metro systems are becoming overly saturated by the ever-increasing travel demand, which results in overcrowded stations, excessive delay, and unsafe anxieties among riders. The concept of extra -long trains (i.e., trains longer than station platforms) was recently proposed in the literature as a promising way to increase a metro line's capacity without additional infrastructure construction. This paper develops a general modeling framework to optimize train block configuration and operation protocols of a metro line so that extra -long trains can be used under varying demand distribution and infrastructure setting. The design problem is formulated as the integration of two coupled vehicle routing problems which simultaneously optimizes the train block configuration plan, door opening strategy, stop skipping strategy, and train dispatch schedule. This paper proposes two customized solution methods, including an adapted savings heuristic and a destroy -andrepair algorithm. A series of hypothetical examples are tested to demonstrate how the proposed solution approaches outperform an existing commercial solver even for small to moderate problem instances. Moreover, two real -world case studies, with very different demand patterns from two continents, are presented to test the effectiveness of using extra -long trains. Our results show that a metro line with extra -long train operations is capable of serving up to 20%-30% more passenger demand as compared to that with only regular trains, while at the same time producing a similar or lower passenger average travel time.
In this research, a robust optimization approach is proposed to the problem of designing emergency response networks for marine oil-spills given uncertainty in the location, size and type of the spill. In this regard,...
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In this research, a robust optimization approach is proposed to the problem of designing emergency response networks for marine oil-spills given uncertainty in the location, size and type of the spill. In this regard, we formulate two robust models (Gamma and Ellipsoidal) to optimize the allocation of response equipment while considering the underlying uncertainty in each oil-spill scenario. An efficient Branch-and-Cut algorithm is then designed to improve the computational performance. The benefits of applying the robust formulations are illustrated and compared to the non-robust model using a realistic case study from Newfoundland (Canada).
Thermal energy storages introduce flexibility into heating systems with numerous advantages on system performance, and operational and maintenance costs. One of the most prominent advantages is the ability to use heat...
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Thermal energy storages introduce flexibility into heating systems with numerous advantages on system performance, and operational and maintenance costs. One of the most prominent advantages is the ability to use heat sources at the operating points with higher efficiency To use the full potential of a thermal energy storage, an adequate control technique is required to control the heat sources connected to it. This paper models a heating system containing a heat source and a thermal energy storage and uses this model for optimal scheduling of the heat source. The optimal schedule is obtained through application of model predictive control which takes into account the efficiency of the heat source. A PI controller is also designed by following practical optima to serve as a baseline for comparison with the MPC-based scheduler. The obtained results show that the optimal scheduler is advantageous compared to the PI controller in terms of both energy efficiency and satisfying the posed constraints.
The inventory routing problem(IRP) is one of the challenging optimization problems in supply chain management(SCM). Inventory Routing Problems currently get a lot of attention, in which a typical property is that inve...
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The inventory routing problem(IRP) is one of the challenging optimization problems in supply chain management(SCM). Inventory Routing Problems currently get a lot of attention, in which a typical property is that inventory control and vehicle routing tasks are taken into account simultaneously. The objective of the IRP is to jointly determine optimal quantities of the product to be delivered to the customers, delivery times and optimal vehicle routes for the shipment of these quantities. At power enterprises, SCM strategies are more and more interesting for the resource optimization. In this paper, a cyclical inventory routing problem is modeled and accounted for one distribution system of waste products at the power stations. This proposed problem is formulated as a linear mixed-integer program, in which the demand rates of customers are assumed to be constant. As to the resource optimization, a practical instance is presented and thoroughly discussed, to illustrate the behavior of the proposed model.
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