The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments

Abstract

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.

Algoritma Artificial Bee Colony untuk Multi Depot Vehicle Routing Problem

“…Perencanaan logistik pasca bencana seharusnya sudah dilaksanakan jauh hari sebelum bencana tersebut terjadi, mulai dari barang logistik bencana, gudang logistik bencana, kendaraan logistik bencana, dan lokasi pengungsian. Saat bencana telah berakhir kebutuhan penting yang harus dipenuhi air, makanan, obat, pakaian, dan tempat perlindungan harus segera dikirim ke titik-titik yang menjadi area yang terdampak bencana tersebut sesuai dengan kebutuhan pengungsi [2].…”

“…Bencana selalu membuat ketidakpastian pada barang kebutuhan bencana yang sering kali tidak seimbangnya antara kebutuhan korban bencana dengan sumberdaya yang dimiliki. Proses perencanaan, mengelola, dan mengontrol sumberdaya yang tersedia untuk menanggulangi kebutuhan korban bencana disebut dengan logistik kemanusiaan [2]. Salah satu indikator dari logistik bencana yang menjadi faktor sukses atau tidaknya penanggulangan bencana tersebut adalah dari sistem logistik bencana [3].…”

Planning of Vehicle Routing with Backup Provisioning Using Wireless Sensor Technologies

“…Wireless sensors have been used for monitoring and tracking in several areas. With regard to their use in smart cities, these can be used to improve traffic control in large cities [13,14], collect information of passenger volume [15], provide optimal routes in real time [16], to reduce greenhouse gas (GHG) emissions [17], in rescue scenarios after a disaster [18] and even to aid the blind [19]. In [15], the system used for data gathering is discussed, but no further planning using such information is done.…”

“…The problem addressed in [17] falls into the category of green vehicle routing problems (GVRP), and the objective is to find routes while minimizing GHG emissions. In rescue scenarios, considered in [18], the demand-related information is quite limited in the initial rescue period and is intuitively unpredictable using historical data, and the emergency resources may be insufficient. The problems addressed in [17,18] are, therefore, different from the one considered in this article.…”

Multi-Depot Vehicle Routing Optimization Considering Energy Consumption for Hazardous Materials Transportation

“…Giosa et al [33] summarized and proposed a number of heuristics for the two-stage approach to solving the MDVRP. In order to solve the emergency vehicle routing problem with multiple depots, Qin et al [34] divided it into two steps, and used the nearest assignment and average distance method to transform the MDVRP into multiple VRPs with a single depot in the first step, and then adopted a genetic algorithm to solve the VRPs with a single depot in the second step. Ho et al [35] developed two hybrid genetic algorithms.…”