Real Time Management in Manufacturing Systems: A State-of-the-art Review - Terminology, Definitions, and Application Areas

The paper presents an introduction to the real time management considering the meta‐theoretical framework for the real time management discipline investigation, the terminology and definitions, and application areas through the state of the art review. The paper presents also some directions for the future work.info:eu-repo/semantics/publishedVersio

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

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

Modelo Matemático e Meta-Heurística Simulated Annealing para Elaboração de Roteiros Turísticos com base no Tourist Trip Design Problem

Muito embora existam diversos pacotes de viagens com destinos predefinidos contemplando locais mais populares, nos últimos anos tem crescido a procura por soluções que criem roteiros personalizados voltados às necessidades de cada turista. Para suprir essa nova demanda surge o Problema de Elaboração de Rotas Turísticas (PERT) ou TouristTrip Design Problem (TTDP) o qual Van Oudheusden e Vansteenwegen (2007) sugerem o uso do OrienteeringProblem (OP) e suas extensões para resolução desta classe de problemas. Esta dissertação tem por objetivo o desenvolvimento de um modelo matemático e de uma meta-heurística SimulatedAnnealing (SA) para resolução do TouristTrip Design Problem (TTDP)

Mixing quantitative and qualitative methods for sustainable transportation in Smart Cities

L'abstract è presente nell'allegato / the abstract is in the attachmen

An optimisation approach for assigning resources to defensive tasks during wildfires

All over the world, wildfires have a big economic, social and environmental impact. It is expected that climate change will result in more frequent, large, catastrophic wildfires. Responding to these large wildfires is a difficult task with high stakes. Incident management teams (IMTs) managing the response to large, escaped wildfires operate in high-pressure environments where they must make complex, time-critical decisions under fast moving, changing conditions. Past research on providing decision support to IMTs focused on modelling initial attack, fire line construction, pre-incident deployment and longer-term planning. However, on days of extreme fire weather, when large fires are burning in hot, dry and windy conditions, fire suppression may be both ineffective and unsafe. The aim of this thesis is to address the problem of assigning resources to alternative tasks besides direct fire suppression. A description of the wildfire resource assignment problem is presented. A mixed-integer programming model is formulated to capture features that are unique to the problem of protecting assets during wildfires. The formulated model generalises the team orienteering problem with time windows, allowing for mixed vehicle types, interchangeable and complementary vehicle capabilities, and travel times which are determined by vehicle specific speed and road network information. The protection requirements of locations are defined in terms of vehicle capabilities. Two approaches are presented to deal with the dynamic nature of wildfire planning: a dynamic rerouting approach and a two-stage stochastic programming approach. The rerouting approach is appropriate when disruptions are unexpected. The aim is to reassign vehicle in a manner that minimises changes to current vehicle assignment. The stochastic approach uses likelihood estimates for fire spread scenarios. Initial vehicle assignments are made in the first stage with the opportunity for adjustments in the second stage based on observed fire-weather outcomes. The proposed approaches resulted in a set of complementary models for wildfire resource assignment. They can, among other, account for mixed vehicle capabilities, handle unexpected changes and incorporate fire spread scenario likelihoods. The models are computationally feasible and have the potential to provide real-time decision support to IMTs