Introduction to stochastic programming

Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones: A survey

In this review, we provide an overview of emerging trends and challenges in the field of intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of perception, planning,...

Planning and Decision-Making for Autonomous Vehicles

https://ir.nctu.edu.tw:443/bitstream/11536/100881/1/982410H009004.PDF

國際期刊 Transportation Research-Part E---Logistics and Transportation Review 特刊編輯補助

Research on dynamic and stochastic vehicle routing problems received increasing interest in the last decade It considers a novel problem class, aiming at an appropriate handling of dynamic events combined with the incorporation of stochastic information about possible future events This survey summarises the recent literature in this area Besides, the classification according to the available stochastic information, a new classification based on the point in time where substantial computational effort for determining decisions or decision policies arises, is introduced Furthermore, the difference in solution quality is analysed between approaches which consider either purely dynamic or stochastic problems compared to those which consider both, stochastic and dynamic aspects A graphical representation demonstrates the strength of the reviewed approaches incorporating dynamic and stochastic information The survey also gives an overview on the intensity of research for the different problem classes and

/pdf/a-survey-on-dynamic-and-stochastic-vehicle-routing-problems-ptztuyno8g.pdf

A survey on dynamic and stochastic vehicle routing problems

The organization of a specialized transportation system to perform transports for elderly and handicapped people is usually modeled as dial-a-ride problem. Users place transportation requests with specified pickup and delivery locations and times. The requests have to be completed under user inconvenience considerations by a specified fleet of vehicles. In the dial-a-ride problem, the aim is to minimize the total travel times respecting the given time windows, the maximum user ride times, and the vehicle restrictions. This paper introduces a dynamic programming algorithm for the dial-a-ride problem and demonstrates its effective application in (hybrid) metaheuristic approaches. Compared to most of the works presented in literature, this approach does not make use of any (commercial) solver. We present an exact dynamic programming algorithm and a dynamic programming based metaheuristic, which restricts the considered solution space. Then, we propose a hybrid metaheuristic algorithm which integrates the dynamic programming based algorithms into a large neighborhood framework. The algorithms are tested on a given set of benchmark instances from the literature and compared to a state-of-the-art hybrid large neighborhood search approach.

/pdf/dynamic-programming-based-metaheuristics-for-the-dial-a-ride-3rl4fezge4.pdf

Dynamic programming based metaheuristics for the dial-a-ride problem

We investigate a so far not examined problem called the Interdependent Lock Scheduling Problem. A Variable Neighborhood Search approach is proposed for finding lock schedules along the Austrian part of the Danube River in order to minimize the overall ship travel times. In computational experiments the performance of our approach is assessed and compared to real-world ship trajectories. Notable improvements can be achieved. In addition, the number of (empty) lockages can be significantly reduced when taking them into account during optimization without loosing too much of quality in travel time optimization.

A Variable Neighborhood Search Approach for the Interdependent Lock Scheduling Problem

Recent developments in telematics, such as the wide spread use of positioning services and mobile communication technologies, allow the exact monitoring of vehicles. These advances build the basis for automatic real-time fleet management systems. To be successful such systems have to rely on optimization algorithms for solving dynamic and stochastic vehicle routing problems based on ingredients such as historical data, stochastic modeling, machine learning, fast shortest-path calculation, fast construction heuristics, and exact and (meta)heuristic optimization methods. This book documents the growing interest in and success of hybrid metaheuristics. They are often used to solve complex and large real-world optimization problems, combining advantages from various fields of computer science and mathematical optimization. Within this chapter the application of such methods for the dynamic and stochastic vehicle routing problem is studied. After a general introduction in this field, the main commonalities of dynamic and stochastic vehicle routing problems are described and a short overview of classical algorithms for these problems is given. Then, in the third part hybrid metaheuristics for dynamic problems vehicle routing problems are be described. The third part focusses on stochastic problems. The fourth part examines the combination of dynamic and stochastic problems. The chapter is concluded with an outlook towards future developments in the field as well as promising open research areas.

Ulrike Ritzinger

Papers

A survey on dynamic and stochastic vehicle routing problems

Dynamic programming based metaheuristics for the dial-a-ride problem

A Variable Neighborhood Search Approach for the Interdependent Lock Scheduling Problem

Hybrid Metaheuristics for Dynamic and Stochastic Vehicle Routing

Bi-objective orienteering for personal activity scheduling