On the Development of a Multilayered Agent-based Heuristic System for Vehicle Routing Problem under Random Vehicle Breakdown

With the recent technological advancement, the Dynamic Vehicle Routing Problem (DVRP) is becoming more applicable but almost all of the research in this field limited the source of dynamism from the order side rather from the vehicle, in addition to the adoption of inflexible tools that are mainly designed for the static problem. Considering multiple random vehicle breakdowns complicates the problem of how to adapt and distribute the workload to other functioning vehicles. In this ongoing PhD research, a proposed multi-layered Agent-Based Model (ABM) along with a modelling framework on how to deal with such disruptive events in a reactive continuous manner. The model is partially constructed and experimented, with a developed clustering rule, on two randomly generated scenario for the purpose of validation. The rule achieved good order allocation to vehicles and reacted to different problem sizes by rejecting orders that are over the model capacity. This shows a promising path in fully adopting the ABM model in this dynamic problem

Disruption Management of ASAE's Inspection Routes

The Rapid development and the emergence of technologies capable of producing real-time data opened new horizons to both planning and optimization of vehicle routes [4]. In this dissertation, the Autoridade de Segurança Alimentar e Económica (ASAE) operation's scenario will be explored and analyzed as a case study to the problem. ASAE is a Portuguese administrative authority specialized in food security and economic auditing and is responsible to regulate thousands of economic entities in the Portuguese territory. ASAE inspections are usually done by brigades using vehicles to inspect economic operators, taking into account their timetables. Previous work on this topic led to the implementation of an inspection route optimization module capable of defining and assigning routes to inspect economic operators, seeking to maximize a utility function. Using optimization algorithms, inspection routes are calculated for each brigade, with information regarding specific map paths and inspection schedules. The approach used does not take into consideration the dynamic properties of real-life scenarios, as the precalculated operation plan is not reviewed in real-time. This work aims to study the dynamic properties of ASAE's operational environment and proposes a solution to efficiently review the precalculated inspection routes and apply the required changes in an appropriate time frame. Vehicle routing problems (VRP) are optimization problems where the aim is to calculate the set of optimized routes for a vehicle fleet, from a starting point to several interesting locations. Dynamic vehicle routing problem (DVRP) is a variant of VRP that makes use of real-time information to calculate the most optimized set of routes at a certain moment [39]. DVRP is a challenging problem because its scope is real-time, meaning that decisions sometimes must be made in short time windows, preventing the use of complex algorithms that require long computational times [10]. The typical approach to this problem is to initially calculate the routes for the whole fleet and dynamically revise the defined operations plan in real-time, once a disruption occurs. This work will model the problem as a DVRP and will compare the performance of heuristics and other modern optimization techniques, proposing a solution that will reduce the impact of disruptions on inspection routes. An optimized operations plan will reduce the time required for inspections, allowing massive economic savings, while reducing a company's ecological footstep. The work can eventually be scaled and used in other institutions, such as GNR or PSP in Portugal, that operate similarly

Dynamic rerouting of vehicles during cooperative wildfire response operations

Incident managers assigning wildfire response vehicles to provide protection to community assets may experience disruptions to their plans arising from factors such as changes in weather, vehicle breakdowns or road closures. We develop an approach to rerouting wildfire response vehicles once a disruption has occurred. The aim is to maximise the total value of assets protected while minimising changes to the original vehicle assignments. A number of functions to measure deviations from the original plans are proposed. The approach is demonstrated using a realistic fire scenario impacting South Hobart, Tasmania, Australia. Computational testing shows that realistic sized problems can be solved within a reasonable time using a commercial solver

Characterizing Logistics Operations Within a Federal Staging Area for Hurricane Response: A Qualitative Analysis of Federal, State and Local Perspectives

A successful deployment of logistics operations following a disaster is a collective contribution of federal, state, and local entities to ascertain an efficient and effective response. This research analyzes data from interviews with disaster response logistics experts from these entities. The objective is to investigate the information sources and planning processes used in these organizations to plan vehicle routes for critical resource deliveries to impacted areas. Special attention is directed to the impacts of incomplete knowledge of infrastructure status, such as road disruptions due to debris or flooding. Supported by both qualitative and quantitative evidence, the study finds that incomplete knowledge of infrastructure status poses serious critical transportation risks such as delivery delays in disaster relief distribution. This research reveals both similarities and differences in logistical decision-making among these organization types and emphasizes the need for improved information sharing and coordination among emergency response organizations. The findings of this research are expected to guide future initiatives aimed at disaster relief routing thereby enhancing emergency response capabilities and outcomes

Characterizing Logistics Operations Within a Federal Staging Area for Hurricane Response: A Qualitative Analysis of Federal, State and Local Perspectives

A successful deployment of logistics operations following a disaster is a collective contribution of federal, state, and local entities to ascertain an efficient and effective response. This research analyzes data from interviews with disaster response logistics experts from these entities. The objective is to investigate the information sources and planning processes used in these organizations to plan vehicle routes for critical resource deliveries to impacted areas. Special attention is directed to the impacts of incomplete knowledge of infrastructure status, such as road disruptions due to debris or flooding. Supported by both qualitative and quantitative evidence, the study finds that incomplete knowledge of infrastructure status poses serious critical transportation risks such as delivery delays in disaster relief distribution. This research reveals both similarities and differences in logistical decision-making among these organization types and emphasizes the need for improved information sharing and coordination among emergency response organizations. The findings of this research are expected to guide future initiatives aimed at disaster relief routing thereby enhancing emergency response capabilities and outcomes

Optimising the climate resilience of shipping networks

Climate catastrophes (e.g. hurricane, flooding and heat waves) are generating increasing impact on port operations and hence configuration of shipping networks. This paper formulates the routing problem to optimise the resilience of shipping networks, by taking into account the disruptions due to climate risks to port operations. It first describes a literature review with the emphasis on environmental sustainability, port disruptions due to climate extremes and routing optimisation in shipping operations. Second, a centrality assessment of port cities by a novel multi-centrality-based indicator is implemented. Third, a climate resilience model is developed by incorporating the port disruption days by climate risks into shipping route optimisation. Its main contribution is constructing a novel methodology to connect climate risk indices, centrality assessment, and shipping routing to observe the changes of global shipping network by climate change impacts

Advanced approach for the public transportation regulation system based on cybercars

International audienceIn the last decade, the authorities require the use of safe, comfortable vehicles to assure a door to door aspect with respect of environment in the urban context. In this paper, we propose an advanced approach of transport regulation where we integrate cybercars into a regulation process as an alternative in disruption cases. For that, we propose an ITS architecture including public transportation and cybercars into the same framework. We will show that collaboration between these two systems provides better results than managing them separably

Route Planning with Dynamic Information from the EPLOS System

The paper presents the problem of distribution route planning with dynamic information about sudden customers\u27 needs. Particular attention was paid to dynamic vehicle route planning and its influence on the distance covered by a distribution vehicle. In the article, authors assume that the quick information about customers’ sudden needs is transferred from the EPLOS tool data base. Authors analyze the available literature on transport route optimization and propose a solution to the problem of distribution among customers with sudden needs. In order to present the impact of quick information influence on the distribution route minimization, a simulation model of the vehicle routing problem was generated in the FlexSim environment