Preemptive priority-based algorithms for fuzzy minimal cost flow problem: An application in hazardous materials transportation

Increased public concern about the transportation of hazardous materials has caused the assurance of safe transport of this material to be a pressing national need. United States Department of Energy (DOE) programs involve the transportation of many hazardous and radioactive materials, and the national need to assure that these materials are transported in a safe manner is being addressed through the application of technology developed as part of the DOE/Albuquerque Operations Office's Transportation Base Technology Program. Currently the Albuquerque Operations Office is the integrator of DOE's Transportation Base Technology Program. Activities in this area include: packaging development, engineering analysis, testing, advanced technology development, packaging certification support, regulatory standards development, information systems management, and risk and systems analysis support. This paper addresses the specifics of DOE activities in these areas.

The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing–Tianjin–Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study.

<p>InSAR can measure surface deformation in all-weather conditions and has been widely used to study landslides, land subsidence, and many geophysical processes. Since the phase of radar echo is measured in 2π rad modulo (wrapped), phase unwrapping is an indispensable step for InSAR, and its reliability directly determines the feasibility of deformation monitoring. However, temporal and spatial decorrelation often leads to severe noises, localized deformation or strong atmospheric turbulence may result in dense fringes, both making traditional unwrapping methods fail in acquiring continual unwrapped phases. Here, we present a deep convolutional neural network (DENet) to identify the probability of phase discontinuities between every two adjacent pixels in the interferogram and apply the probability as cost in the widely-used minimal cost flow solver to achieve phase unwrapping. To train the network effectively, we design a simulation strategy to generate sufficient training samples: the terrain-related phases are used as the background phases, and the deformation phases, atmospheric turbulence phases, and noises are superimposed to build the training samples. Unlike classical methods such as GAMMA and SNAPHU that use the coherence map as the quality index, we use the probability of phase discontinuities estimated by the DENet as the arc-cost of the minimum cost flow problem. We apply the proposed method to unwrap simulated and real interferograms and compare the results with 8 existing methods (including traditional and deep learning-based ones).  On the simulated data set, the root-mean-square error (RMSE) of the proposed method is lower than all the 8 existing methods. We also test different methods to unwrap the real Sentinel-1 interferograms and verified the reliability using ALOS-2 data with a nearly identical acquisition period. Our results show strong robustness and stability when unwrapping very large interferograms with complicated phase patterns. The proposed method takes advantages of both deep learning and traditional minimal cost flow solver, which can effectively unwrap interferograms with low coherence and/or dense fringes, providing strong potential for large-scale SAR interferometry applications.</p>

This paper presents a variant of vehicle routing problem, incorporating factors of transportation costs in conjunction with adverse situations. The effects of hazardous materials (HazMat) transportation are examined on air-pollution exposure levels, as well as the risk and damage in the case of accidents. In an urban network, the various weights that can be are assigned to each road of a route are associated to the following factors: time, cost, pollution exposure levels, and the risk of damage in HazMat transportation. These weights express the travel cost and the estimated provoked adverse consequences at each road of a vehicle transit route between two disparate points of the network concerning the pollution and risk of unforeseen accident during hazardous materials transportation. The sum of the weights assigned to every road of a route represents the route value according to the corresponding factors. We introduce an optimization criterion in order to select the optimal route among all vehicle transition routes joining any given pair of the network points that does not surpass a predefined threshold route value for each factor. The predefined weights for each factor are a percentage increment of its corresponding shortest route value. The optimal location of a central depot is determined where each vehicle serves a customer using one specific route with respect to the posed restrictions. Subsequently, a suitable partition into sub-networks is carried out in the case of large urban areas and a depot is assigned to each sub-network by applying a specific optimization criterion. A branch and bound tree search algorithm is developed for the determination of the optimal routes while the locations of the depots are investigated within the framework of graph theory. Finally, small numerical examples are given.

In this paper, we present a new strongly polynomial time algorithm for the minimum cost flow problem, based on a refinement of the Edmonds-Karp scaling technique. Our algorithm solves the uncapacitated minimum cost flow problem as a sequence of O(n log n) shortest path problems on networks with n nodes and m arcs and runs in O(n log n(m + n log n)) time. Using a standard transformation, this approach yields an O(m log n(m + n log n)) algorithm for the capacitated minimum cost flow problem. This algorithm improves the best previous strongly polynomial time algorithm, due to Z. Galil and E. Tardos, by a factor of n2/m. Our algorithm for the capacitated minimum cost flow problem is even more efficient if the number of arcs with finite upper bounds, say m′, is much less than m. In this case, the running time of the algorithm is O((m′ + n) log n(m + n log n)).

Hazardous material transportation is one of the main concerns due to the nature of hazardous materials and their incident impacts. In general, transport risk is a main attribute to develop mathematical models for hazardous material routing problem as well as network designing or improving road safety. This paper presents a chaotic-simulation based model to determine the high selected links to improve road network quality for hazardous material transportation, in which risk is considered as a chaotic variable over the network whereas a simulation technique has been applied to cover a wide range of selecting paths. A real road network, consists of fifty-nine nodes and eighty two-way edges, is used for running the mathematical model and checking validation. Due to the large amounts of hazardous material transported by trucks, the proposed methodology is focused on fuel transportation, and high selected list of edges (links) has been obtained to improve road safety. Sensitivity analysis revealed that using different seeds for generating transport risk has no significant effects on finding the most frequent paths and high selected edges.

Abstract: The subject of the article are regulations regarding transport of hazardous materials in road transportation. In Poland, as well as in most European countries, these regulations are mainly governed by the ADR Agreement, which is a supra-national legal act. The article contains an analysis of the mentioned legal act. Despite the fact that the ADR Agreement harmonizes regulations concerning the transport of hazardous materials, there are domestic standards that differ slightly from the provisions of this agreement. The article also describes parking facilities for vehicles carrying hazardous materials in Poland and presents statistical data regarding parking spaces for this type of vehicles. Keywords: Road transport; Hazardous materials; ADR Agreement; Parking spaces; MOP

Increasing industrialization and globalization has spawned the unprecedented generation of environmental toxic and hazardous wastes. The existence of publicly known hazardous waste problems such as toxic spills, and river pollution that pose serious and very real threats to human health puts extensive pressure on the government to take an aggressive role in hazardous waste control and transportation. The main objective of hazardous waste transportation is public safety. Each government has the responsibility to ensure that hazardous materials should be transported safely for the social and economic good of the country. Hazardous waste management is now a major and urgent global concern. Various techniques, models, and guidelines for the perception of risks associated with the transport of the hazardous materials are developed. Database of the accident data are developed by transportation agencies to be used for the development of models to improve safety of hazardous waste transportation. Based on the available risk perception models, accident models, the type of hazardous material, origin/destination, and the availability of emergency response routes for their transport are properly designed. Advanced technologies, automated vehicle location system (AVL) and geographical information system (GIS) are also used for the analysis and modeling for the safe transport of hazardous materials. The purpose of this project is to present a literature review of hazardous waste materials and their impact on human health, regulations to control the movement of hazardous materials, Basel Convention and its effectiveness, treatment and disposal of hazardous materials, model developments for risk perception and management and the use of advanced technologies for safe transportation of hazardous wastes. Based on the literature review, the conclusions and future recommendations for possible improvement of the models and techniques used for safe transportation of hazardous wastes are presented.

Optimal network design and storage management in petroleum distribution network under uncertainty

In order to minimize the occurrence of large-scale accidents resulting from the transportation of hazardous materials (HAZMAT) on urban roadways, a system to monitor freight vehicle movements in real-time is being implemented. Although monitoring systems are in place, no prioritization strategy has been prepared for the selection of vehicles by the companies handling HAZMAT. Therefore, this study aims to analyze the factors affecting the level of transport management of HAZMAT handling business entities such as the freight, shipping, and vehicle characteristics, and suggests directions for effective policy enforcement of HAZMAT vehicle monitoring strategies. In this study, nation-wide survey data on the logistics status of HAZMAT handling business entities were collected, and the influence of such business entities according to their level of transport management was derived using an ordered logit model. Implications were obtained through statistical analysis of the transport management behavior of urban hazardous material handling business entities. In the future, it is necessary to study empirical methods for setting priorities based on the survey data of the entire population of HAZMAT transport vehicles.

In rider demand responsive systems riders submit requests to demand transit services and the incoming requests and vehicles are matched by the system. This demand-responsive transport problem is viewed by existing research as a kind of spatial matching problem between vehicles and riders. However, existing schemes mainly focus on maximizing the number of matching pairs. It neglects other factors like the length of pickup trajectories and riders’ waiting time. And the matching is not revocable, which loses the chance for further optimizations. Moreover, there is still not much work on handling and matching the appointment-based requests that play a key role in the demand-responsive transport market. In this article, we propose an algorithm called BMCF ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Bipartite Minimal-Cost Flow</i> ) to solve the taxi-rider matching problem with appointment-based rider requests on a time-dependent road network. Unlike existing solutions that map the problem into the max flow problem, we transform the optimal matching to a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">minimal cost flow problem</i> which aims to maximize a utility value and could be solved efficiently. Riders and vehicles are modeled as vertices in a bipartite graph, and factors like the length of pickup trajectories, riders’ waiting time, etc. are abstracted as utilities and denoted as weights of the edges which are taken into account during the matching process. To the best of our knowledge, the proposed scheme is the first to efficiently integrate and process both the real-time and appointment-based requests within the same framework, and the assignments between vehicles and requests could be dynamically adjusted and revoked to maximise the overall utility. Experimental results show that the proposed algorithm can effectively increase the appointment-based matching ratio and decrease the riders’ waiting time (> 10.4%) and vacant vehicles’ picking up time (> 60.9%) compared with existing schemes, while at the cost of acceptable increase on the running time.

System optimal dynamic traffic assignment: Properties and solution procedures in the case of a many-to-one network

Medical Physicists are frequently involved in shipping radioactive materials or supervising those who do. Current U.S. Department of Transportation Hazardous Material Regulations, 49 CFR Parts 171 – 185, require hazmat employees to have documented training specified in 49 CFR 171 Subpart H. A hazmat employee is defined as an individual who: (1) loads, unloads or handles hazardous material; (2) manufactures, tests, reconditions, repairs, modifies, marks or otherwise represents containers, drums or packagings as qualified for use in the transportation of hazardous materials; (3) prepares hazardous materials for transportation; (4) is responsible for safety of transporting hazardous materials; or (5) operates a vehicle used to transport hazardous materials. Recurrent training is required at least once every three years. (The IATA two year training interval is not applicable and is generally misunderstood.) FAA has escalated inspection and enforcement and facilities who ship radiopharmaceuticals to other laboratories, return radiopharmaceuticals or radioactive sources to suppliers or otherwise ship radioactive materials have been cited for failure to provide and documents this training. The course will cover typical shipments by air and highway which are encountered in a medical institution. Items such as fissile materials, highway route controlled quantities, rail shipments, vessel shipments and such will be omitted, although specific questions may be addressed. A major objective of the course is to provide the process of shipping radioactive material in a sequential and logical fashion. Radioactive material shipments of excepted packages and Type A packages will be emphasized. The new exempt material activity concentrations and exempt consignment activity limits will be presented, as well as the new international proper shipping names and UN numbers which become mandatory on October 1, 2004. The program is designed to meet the DOT training requirements, but it is the hazmat employer's responsibility to ensure that each hazmat employee is properly trained. It is the hazmat employer's responsibility to determine the degree to which this course meets the employer's requirements, including contents of the course and the examination. Participants will gain sufficient knowledge to prepare training programs for others in their institutions. Handouts will summarize the course. A feature handout is a composite table which provides A1, A2, RQ, Exempt Concentration, and Exempt Consignment values in a single table in both Becquerel and Curie units. The examination at the conclusion will be self graded in the course and retained by the participant to form part of his training documentation. Certification of course attendance will be through the AAPM CEU documentation system.

Abstract. Radioactive, toxic, smother, flammable, and explosive materials in solid, liquid or gas states which can negatively impact goods, organisms, and most importantly humans are called as “Hazardous Materials”. Hazardous material transportation and storage carry risk factors in addition to their other types of transportation operations. Furthermore, selection of a suitable warehouse becomes a problematic issue in which multiple criteria are evaluated as paying attention to risky circumstances. In this context, hazardous material warehouse selection is considered as a multiple criteria decision problem in our study. In particularly, for the explosives storage among other hazardous materials, necessary criteria are determined according to expert’s consultant. The determined criteria are weighted according to decision makers’ consultancy and the alternatives are evaluated by fuzzy MULTIMOORA under uncertainty throughout the decision making process in the study.. The proposed approach is discussed on a case study. Keywords. Fuzzy MULTIMOORA, Warehouse Selection, Hazardous Materials. JEL. D81 , R53, C40, C44.

To comprehensively understand the research progress of the fleet scheduling for hazardous materials, the study has summarized the corresponding research results from three aspects (a) hazardous materials transportation risk, (b) route optimization, and (c) fleet scheduling, and then pointed out potential problems from six aspects: (a) the coupling risk of the transport fleet; (b) the screening of time and space for the transport of hazardous materials; (c) the scheduling optimization for transport fleets; (d) taking insufficient account of transport risks fairness; (e) insufficient robustness of scheduling schemes; and (f) lacking of research results on fleet scheduling of transport in the context of antiterrorism. After that, by considering the existing shortcomings of the current research, five research directions are presented that should be further explored in the future. Subsequently, both rough set and association rule theory is applied to explore the cause chain of transportation accidents for hazardous materials, and analyze the mechanism of transport accident for hazardous materials. Next, the Bayesian network is presented to predict the accident rate of hazardous materials transportation under different temporal and spatial conditions, and the dynamic rolling scheduling method of hazardous materials transport fleet is constructed under normal and antiterrorism background.