Applying genetic algorithms to convoy scheduling

We present the results of our work on applying genetic algorithms combined with a discrete event simulation to the problem of convoy scheduling. We show that this approach can automatically remove conflicts from a convoy schedule thereby providing to the human operator the ability to search for better solutions after an initial conflict free schedule is obtained. We demonstrate that it is feasible to find a conflict free schedule for realistic problems in a few minutes on a common workstation or laptop. The system is currently being integrated into a larger Transportation Information System that regulates highway movement for the militaryIFIP International Conference on Artificial Intelligence in Theory and Practice - Industrial Applications of AIRed de Universidades con Carreras en Informática (RedUNCI

Applying genetic algorithms to convoy scheduling

We present the results of our work on applying genetic algorithms combined with a discrete event simulation to the problem of convoy scheduling. We show that this approach can automatically remove conflicts from a convoy schedule thereby providing to the human operator the ability to search for better solutions after an initial conflict free schedule is obtained. We demonstrate that it is feasible to find a conflict free schedule for realistic problems in a few minutes on a common workstation or laptop. The system is currently being integrated into a larger Transportation Information System that regulates highway movement for the militaryIFIP International Conference on Artificial Intelligence in Theory and Practice - Industrial Applications of AIRed de Universidades con Carreras en Informática (RedUNCI

Applying genetic algorithms to convoy scheduling

We present the results of our work on applying genetic algorithms combined with a discrete event simulation to the problem of convoy scheduling. We show that this approach can automatically remove conflicts from a convoy schedule thereby providing to the human operator the ability to search for better solutions after an initial conflict free schedule is obtained. We demonstrate that it is feasible to find a conflict free schedule for realistic problems in a few minutes on a common workstation or laptop. The system is currently being integrated into a larger Transportation Information System that regulates highway movement for the militaryIFIP International Conference on Artificial Intelligence in Theory and Practice - Industrial Applications of AIRed de Universidades con Carreras en Informática (RedUNCI

Optimization of Military Convoy Routing

Motoriseeritud rännakukolonnide optimeerimine on matemaatilise optimeerimise probleem, milles püütakse leida optimaalset marsruutimislahendust ja vastavat ajakava samaaegsetelt liikuvatele rännakukolonnidele. Käesolevas töös luuakse valik erinevatel optimeerimistehnikatel põhinevaid meetodeid, mida testides püütakse leida parimat Eesti oludele vastavat rännakukolonnide marsruutimise optimeerimismeetodit. Häid tulemusi saavutati kasutades osalise täisarvulise planeerimise mudelit koos heuristiliste täiendustega, rakendades jaga-ja-piira tehnikal põhinevat täpset algoritmi, kui ka kasutades fikseeritud järjestusega marsruutimislahendust. Lisaks töötati bakalaureusetöö koostamise käigus välja optimeerimismeetodeid kasutav rakendus, mille abil on võimalik võrrelda erinevate meetodite käitumist ja omadusi, esitada arvutuste tulemusena leitud teekondi ja ajagraafikuid ning animeerida Eesti kaardil rännakukolonnide liikumist. Töö tulemusena võib väita, et matemaatilise optimeerimise meetodid on sobivad päriseluliste rännakukolonnide optimeerimisprobleemide kiireks ja kvaliteetseks lahendamiseks ja et neid meetodeid kasutades on võimalik parandada rännakukolonnide kavandamisel tehtavate planeerimisotsuste kvaliteeti.Convoy movement problem is a mathematical optimization problem which tries to find optimal routing and scheduling solution for concurrent military convoy movements. In this thesis several optimization methodologies are designed and tested to find best suited algorithm for solving practical convoy routing instances in Estonia. Encouraging results are obtained by using a mixed integer programming model together with simple heuristics, by creating an exact branch-and-bound methodology and by developing fixed-order based routing approach. Bachelor’s thesis also provides a complementary application to compare qualities of designed methods, to present calculated routes and schedules and to display convoy movement animations on the map of Estonia. Thesis illustrates that methods of mathematical optimization can be used to solve realworld instances of convoy movement problem fast and with quality results and hence improve decisionmaking in operational convoy planning practice

Revitalising the Single Batch Environment: A 'Quest' to Achieve Fairness and Efficiency

In the realm of computer systems, efficient utilisation of the CPU (Central Processing Unit) has always been a paramount concern. Researchers and engineers have long sought ways to optimise process execution on the CPU, leading to the emergence of CPU scheduling as a field of study. This research proposes a novel algorithm for batch processing that operates on a preemptive model, dynamically assigning priorities based on a robust ratio, employing a dynamic time slice, and utilising periodic sorting technique to achieve fairness. By engineering this responsive and fair model, the proposed algorithm strikes a delicate balance between efficiency and fairness, providing an optimised solution for batch scheduling while ensuring system responsiveness

Dispatching and Rescheduling Tasks and Their Interactions with Travel Demand and the Energy Domain: Models and Algorithms

Abstract The paper aims to provide an overview of the key factors to consider when performing reliable modelling of rail services. Given our underlying belief that to build a robust simulation environment a rail service cannot be considered an isolated system, also the connected systems, which influence and, in turn, are influenced by such services, must be properly modelled. For this purpose, an extensive overview of the rail simulation and optimisation models proposed in the literature is first provided. Rail simulation models are classified according to the level of detail implemented (microscopic, mesoscopic and macroscopic), the variables involved (deterministic and stochastic) and the processing techniques adopted (synchronous and asynchronous). By contrast, within rail optimisation models, both planning (timetabling) and management (rescheduling) phases are discussed. The main issues concerning the interaction of rail services with travel demand flows and the energy domain are also described. Finally, in an attempt to provide a comprehensive framework an overview of the main metaheuristic resolution techniques used in the planning and management phases is shown

Optimization of Energy-Efficient Speed Profile for Electrified Vehicles

This work presents a study of the energy-efficient operation of all-electric vehicles leveraging route information, such as road grade, to adjust the velocity trajectory Minimization of energy consumption is one of the main targets of research for both passenger vehicles in terms of economic benefit, and army vehicles in terms of mission success and decision making. The optimization of a speed profile is one of the tools used to achieve energy minimization and it can also help in the useful utilization of autonomy in vehicles. The optimization of speed profile is typically addressed as an Optimal Control Problem (OCP). The obstacle that disrupts the implementation of optimization is the heavy computational load that results from the number of state variables, control inputs, and discretization, i.e., the curse of dimensionality. In this work, Pontryagin's Maximum Principle (PMP) is applied to derive necessary conditions and to determine the possible discrete operating modes. The analysis shows that only five modes are required to achieve minimum energy consumption; full propulsion, cruising, coasting, full regeneration, and full braking. Then, the problem is reformulated and solved in the distance domain using Dynamic Programming to find the optimal speed profiles. Various simulation results are shown for a lightweight autonomous military vehicle. Army Programs use various drive cycles including time, speed, and grade, for testing and validating new vehicle systems and models. Among those cycles, two different drive conditions are studied: relatively flat, Convoy, and hilly terrain, Churchville B. For the Convoy cycle, the optimal speed cycle uses 21% less energy for the same trip duration or reduces the time by 14% with the same energy consumption while for the Churchville B cycle, it uses 24% less energy or provides 24% reduction in time. Furthermore, the sensitivity of energy consumption to regenerative-braking power limits and trip time is investigated. These studies provide important information that can be used in designing component size and scheduling operation to achieve the desired vehicle range. Lastly, the work provides parametric studies about the influence of the efficiency of an electric motor on performance including energy consumption and control modes.Master of Science in EngineeringAutomotive Systems Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/146793/1/Hadi_Abbas_Thesis (1).pdfDescription of Hadi_Abbas_Thesis (1).pdf : Thesi

Designing and Scheduling Cost-Efficient Tours by Using the Concept of Truck Platooning

Truck Platooning is a promising new technology to reduce the fuel consumption by around 15% via the exploitation of a preceding and digitally connected truck’s slipstream. However, the cost-efficient coordination of such platoons under consideration of mandatory EU driving time restrictions turns out to be a highly complex task. For this purpose, we provide a comprehensive literature review and formulate the exact EU-Truck Platooning Problem (EU-TPP) as an Integer Linear Program (ILP) which also features a hypothetical task-relieving effect for following drivers in a convoy. In order to increase the computational efficiency, we introduce an auxiliary constraint and two hierarchical planning-based matheuristic approaches: the Shortest Path Heuristic (SPH) and the Platoon Routing Heuristic (PRH). Besides a qualitative sensitivity analysis, we perform an extensive numerical study to investigate the impact of different critical influence factors on platooning, being of major political and economic interest. Our experiments with the EU-TPP suggest remarkable fuel cost savings of up to 10.83% without a 50% task relief, while its inclusion leads to additional personnel cost savings of up to even 31.86% at best with maximally 12 trucks to be coordinated in a recreated part of the European highway network. Moreover, we prove our matheuristics’ highly favorable character in terms of solution quality and processing time. Keywords: autonomous transport; Truck Platooning; driving time and rest periods; cost-efficient routing & scheduling; computational efficiency