a fast heuristic for routing in post disaster humanitarian relief logistics

Abstract In the last decades, natural disasters have been affecting the human life of millions of people. The impressive scale of these disasters has pointed out the need for an effective management of the relief supply operations. One of the crucial issues in this context is the routing of vehicles carrying critical supplies and help to disaster victims. This problem poses unique logistics challenges, including damaged transportation infrastructure and limited knowledge on the road travel times. In such circumstances, selecting more reliable paths could help the rescue team to provide fast services to those in needs. The classic cost-minimizing routing problems do not properly reflect the relevant issue of the arrival time, which clearly has a serious impact on the survival rate of the affected community. In this paper, we focus specifically on the arrival time objective function in a multi-vehicle routing problem where stochastic travel times are taken into account. The considered problem should be solved promptly in the aftermath of a disaster, hence we propose a fast heuristic that could be applied to solve the problem

A fast heuristic for routing in post-disaster humanitarian relief logistics

In the last decades, natural disasters have been affecting the human life of millions of people. The impressive scale of these disasters has pointed out the need for an effective management of the relief supply operations. One of the crucial issues in this context is the routing of vehicles carrying critical supplies and help to disaster victims. This problem poses unique logistics challenges, including damaged transportation infrastructure and limited knowledge on the road travel times. In such circumstances, selecting more reliable paths could help the rescue team to provide fast services to those in needs. The classic cost-minimizing routing problems do not properly reflect the relevant issue of the arrival time, which clearly has a serious impact on the survival rate of the affected community. In this paper, we focus specifically on the arrival time objective function in a multi-vehicle routing problem where stochastic travel times are taken into account. The considered problem should be solved promptly in the aftermath of a disaster, hence we propose a fast heuristic that could be applied to solve the problem

Randomized Load Balancing under Loosely Correlated State Information in Fog Computing

Fog computing infrastructures must support increasingly complex applications where a large number of sensors send data to intermediate fog nodes for processing. As the load in such applications (as in the case of a smart cities scenario) is subject to significant fluctuations both over time and space, load balancing is a fundamental task. In this paper we study a fully distributed algorithm for load balancing based on random probing of the neighbors' status. A qualifying point of our study is considering the impact of delay during the probe phase and analyzing the impact of stale load information. We propose a theoretical model for the loss of correlation between actual load on a node and stale information arriving to the neighbors. Furthermore, we analyze through simulation the performance of the proposed algorithm considering a wide set of parameters and comparing it with an approach from the literature based on random walks. Our analysis points out under which conditions the proposed algorithm can outperform the alternatives

Optimization of Heliostat Field in a Thermal Solar Power Plant with an Unfired Closed Joule-Brayton Cycle

Abstract In the last decades, concentrating solar power (CSP) has been gaining increasing attention as a sustainable technology for producing electricity. Nowadays, in the world, 483.6 MWs are produced by CSP plants of which 457 MW are already in commercial stage, whereas the other 430 MWs are under construction. In this paper, a solar tower with an unfired closed Joule-Brayton cycle of 10 MW peak power, located in Seville, is analyzed. The cycle, that employs only atmospheric air, without fuel consumption, relies on the possibility to vary the mean density of the air flowing in the plant. By using an auxiliary compressor and a bleed valve, a variable mass flow rate can be obtained so to keep the temperature at turbine inlet constant. On the other hand, in the concentrated solar plant, the number of installed heliostats can reflect towards the receiver the nominal thermal power, even with reduced values of the DNI. With the increase of the radiation, when the thermal energy flux achieves the limit tolerable by the receiver, a part of heliostats is defocused. On the contrary, in the presence of transients, due, for example, to clouds or in case of low solar radiation, the mirrors will be all, or in part, oriented towards the receiver face, so to keep constant the receiver outlet air temperature at the design value. Both the above mentioned control systems, without any fuel addition, act with the common goal of maintaining constant the air temperature at turbine inlet. However, they intervene at different times: at rated power, heliostats work, while the air flow rate is kept constant at the maximum value; when the nominal conditions are no longer achievable (the DNI values are insufficient), the adjustment is performed through the modulation of the pressure base control system, focusing the entire surface of the mirrors on the receiver. The analysis shows how the interaction between these systems influences the number and size of heliostats to be installed in the solar field. The study of the state of art has demonstrated that, in tower systems currently in operation, without storage, a solar multiple of 1.3 is generally used; our contribution shows how, with the air density control system, this value may be reduced, with consequent benefit on the heliostats cost. The numerical tests have been carried out by using the WINDELSOL software to optimize the heliostat field configuration and the THERMOFLOW, for the thermodynamic analysis

A multi-period location-allocation model for nursing home network planning under uncertainty

This paper proposes a multi-period location- allocation problem arising in nursing home network planning. We present a strategic model in which the improvement of service accessibility through the planning horizon is appropriately addressed. Unlike previous research, the proposed model modifies the allocation pattern to prevent unacceptable deterioration of the accessibility criterion. In addition, the problem is formulated as a covering model in which the capacity of facilities as well as the demand elasticity are considered. The uncertainty in demands within each time period is captured by adopting a distributionally robust approach. The model is then applied to a real case study for nursing home planning network in Shiraz city, Iran

Genome-wide distribution of 5-formylcytosine in embryonic stem cells is associated with transcription and depends on thymine DNA glycosylase

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.EAR is a Herchel Smith Fellow. MB and HB are supported by the Centre for Trophoblast Research, MB is a Next Generation Research Fellow. MJB is supported by a BBSRC studentship. The WR lab is supported by BBSRC, MRC, the Wellcome Trust, EU EpiGeneSys and BLUEPRINT. The SB lab is supported by core funding from Cancer Research UK

Mixed integer programming in production planning with backlogging and setup carryover : modeling and algorithms

This paper proposes a mixed integer programming formulation for modeling the capacitated multi-level lot sizing problem with both backlogging and setup carryover. Based on the model formulation, a progressive time-oriented decomposition heuristic framework is then proposed, where improvement and construction heuristics are effectively combined, therefore efficiently avoiding the weaknesses associated with the one-time decisions made by other classical time-oriented decomposition algorithms. Computational results show that the proposed optimization framework provides competitive solutions within a reasonable time

A survey on probabilistic broadcast schemes for wireless ad hoc networks

Broadcast or flooding is a dissemination technique of paramount importance in wireless ad hoc networks. The broadcast scheme is widely used within routing protocols by a wide range of wireless ad hoc networks such as mobile ad hoc networks, vehicular ad hoc networks, and wireless sensor networks, and used to spread emergency messages in critical scenarios after a disaster scenario and/or an accidents. As the type broadcast scheme used plays an important role in the performance of the network, it has to be selected carefully. Though several types of broadcast schemes have been proposed, probabilistic broadcast schemes have been demonstrated to be suitable schemes for wireless ad hoc networks due to a range of benefits offered by them such as low overhead, balanced energy consumption, and robustness against failures and mobility of nodes. In the last decade, many probabilistic broadcast schemes have been proposed by researchers. In addition to reviewing the main features of the probabilistic schemes found in the literature, we also present a classification of the probabilistic schemes, an exhaustive review of the evaluation methodology including their performance metrics, types of network simulators, their comparisons, and present some examples of real implementations, in this paper

Integrating production scheduling and transportation procurement through combinatorial auctions

This study uses the winner determination problem (WDP) to integrate auction transportation procurement with decisions related to production scheduling. The basic problem arises when a manufacturer has to clear a combinatorial auction to decide whether to cover transportation needs by using the in-house fleet or to procure transportation through auction. Thus, the manufacturer should include an additional decision level by integrating the WDP with production scheduling to gain efficiency and achieve savings in the logistics system. To the best of our knowledge, this is the first time production and transportation procurement problems are being solved simultaneously in an integrated manner. The study proposes a mathematical formulation and develops two heuristic approaches for solving the integrated problem. Extensive computational experiments and sensitivity analyses are reported to validate the model, assess the performance of the heuristics, and show the effect of integration on total cost. © 2020 The Authors. Networks published by Wiley Periodicals LLC