Hazardous materials: An inventory model with risk and safety considerations

Hazardous materials (HAZMAT) are essential to the economy in different industrial processes for the operation of different machines and systems. However, these materials also represent a risk to people, property, and the environment. A literature review was conducted to observe the approaches and considerations that have been taken into account in previous research related to HAZMAT inventory management. As a result, it was observed that most of the studies do not take into account risk considerations, the presence of fire protection systems, or regulatory compliance. The most common objective of the reviewed articles is to minimize the total inventory cost of the HAZMAT inventories. The main objective of this research is to develop an inventory model that allows the determination of the order quantities of HAZMAT that have to be purchased and the inventory risk level. This model will consider the maximum allowable quantities indicated by the U.S. HAZMAT regulations for transportation, storage, and fire protection systems, to provide regulatory compliance. To create the HAZMAT inventory model, modifications to the classic economic order quantity model have been made considering the existing HAZMAT regulations such as the International Building Code and the 49 C.F.R. by the Department of Transportation. An interactive tool has been developed to allow the user to use the proposed model. In addition, the proposed HAZMAT inventory model with risk and safety considerations will allow users to understand the impact of the different inventory conditions such as the type of occupancy of the facility and the type of fire protection system on the order quantity and the inventory risk level

Fairness in hazmat routing-scheduling: a bi-objective Stackelberg game

We investigate a hazmat routing-scheduling problem. To minimize the overall expected risk, various vehicles may take different routes/schedules to avoid multiple accidents on the same link. Therefore, the company envisages two issues: (1) unfairly, a vehicle departing earlier from its origin may arrive earlier at its destination than the others leaving later; (2) focusing only on the minimization of risk may increase travel time/cost incurred by the company. We suggest a bi-objective game-theoretic formulation and solve it by a modified Adaptive Large Neighborhood Search and Simulated Annealing. We test the solution on a real-life case and extract practical insights

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man