Scatter Search Applied to the Vehicle Routing Problem with Simultaneous Delivery and Pickup

Maquera, Gladys; Laguna, Manuel; Gandelman, Dan Abensur; Sant’Anna, Annibal Parracho

doi:10.4018/978-1-4666-2145-9.ch010

Cited by 2 publications

(2 citation statements)

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“…Constraint (15) ensures that one demand point can be serviced only by one vehicle. Constraint (16) represents the domain of the decision variable.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Berghida and Boukra [15] dealt with the vehicle routing problem with simultaneous pickup and delivery Sustainability 2017, 9, 288 3 of 24 by a new technique based on a cooperative approach reaping the benefits of three metaheuristics. Maquera et al [16] presented an application of scatter search to the problem of routing vehicles that are required to deliver and pickup goods, which generates all pairs of solutions that contain at least one new element.…”

Section: Introductionmentioning

confidence: 99%

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The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments

Qin

Cheng

et al. 2017

Sustainability

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Abstract:The reasonable utilization of limited resources is critical to realize the sustainable developments. In the initial 72-h crucial rescue period after the disaster, emergency supplies have always been insufficient and the demands in the affected area have always been uncertain. In order to improve timeliness, utilization and sustainability of emergency service, the allocation of the emergency supplies and the emergency vehicle routes should be determined simultaneously. Assuming the uncertain demands follow normal distribution, an optimization model for the emergency vehicle routing, by considering the insufficient supplies and the uncertain demands, is developed. The objective function is applied to minimize the total costs, including the penalty costs induced by more or less supplies than the actual demands at all demand points, as well as the constraints of the time windows and vehicle load capacity taken into account. In more details, a solution method for the model, based on the genetic algorithm, is proposed, which solves the problem in two stages. A numerical example is presented to demonstrate the efficiency and validity of the proposed model and algorithm.

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“…Constraint (15) ensures that one demand point can be serviced only by one vehicle. Constraint (16) represents the domain of the decision variable.…”

Section: Mathematical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%