Ladimer S. Nagurney

Environmental Impact Assessment of Transportation Networks with Degradable Links in an Era of Climate Change

ABSTRACT This paper proposes environmental impact assessment indices to evaluate the environmental effects of link capacity degradation in transportation (road) networks. The indices are applicable in the case of either user-optimizing or system-optimizing behavior. We also construct environmental link importance indicators that allow for the ranking of links in transportation networks in terms of their environmental importance, should they be removed/destroyed. Numerical transportation network examples illustrate the proposed quantitative environmental indicators and further substantiate that system-optimizing behavior does not necessarily lead to reduced emissions.

Software defined radio in the electrical and computer engineering curriculum

The development of Software Defined Radio systems and their extension to Cognitive Radio Systems and Smart Radio Systems have introduced a plethora of topics and examples that can be included in the curriculum. The design of these software defined radio systems has less in common with traditional radio design and more in common with the design of Embedded Systems and Software Engineering. This purpose of this paper is to overview software defined radio from the simplest form to its most complicated form and giveexamples on how software defined radio concepts can be used as examples and exercises in a variety of Electrical Engineering and Computer Engineering courses and labs.

Pharmaceutical Supply Chain Networks with Outsourcing Under Price and Quality Competition

In this paper, we present a pharmaceutical supply chain network model with outsourcing under price and quality competition, in both equilibrium and dynamic versions. We consider a pharmaceutical firm that is engaged in determining the optimal pharmaceuti- cal flows associated with its supply chain network activities in the form of manufacturing and distribution. In addition to multimarket demand satisfaction, the pharmaceutical firm seeks to minimize its total cost, with the associated function also capturing the firms weighted disrepute cost caused by possible quality issues associated with the contractors. Simulta- neously, the contractors, who compete with one another in a noncooperative manner in prices a la Bertrand, and in quality, seek to secure manufacturing and distribution of the pharmaceutical product from the pharmaceutical firm. This game theory model allows for the determination of the optimal pharmaceutical product flows associated with the supply chain in-house and outsourcing network activities and provides the pharmaceutical firm with its optimal make-or-buy decisions and the optimal contractor-selections. We state the gov- erning equilibrium conditions and derive the equivalent variational inequality formulation. We then propose dynamic adjustment processes for the evolution of the product flows, the quality levels, and the prices, along with stability analysis results. The algorithm yields a discretization of the continuous-time adjustment processes. We present convergence results and compute solutions to numerical examples to illustrate the generality and applicability of the framework.

A Supply Chain Game Theory Framework for Cybersecurity Investments Under Network Vulnerability

In this paper, we develop a supply chain game theory framework consisting of retailers and consumers who engage in electronic transactions via the Internet and, hence, may be susceptible to cyberattacks. The retailers compete noncooperatively in order to maximize their expected profits by determining their optimal product transactions as well as cybersecurity investments in the presence of network vulnerability. The consumers reveal their preferences via the demand price functions, which depend on the product demands and on the average level of security in the supply chain network. We prove that the governing Nash equilibrium conditions of this model can be formulated as a variational inequality problem, provide qualitative properties of the equilibrium product transaction and security investment pattern, and propose an algorithm with nice features for implementation. The algorithm is then applied to two sets of numerical examples that reveal the impacts on the equilibrium product transactions, the security levels, the product prices, the expected profits, and the retailer vulnerability as well as the supply chain network vulnerability, of such issues as: increased competition, changes in the demand price functions, and changes in the security investment cost functions.

Spatial price equilibrium with information asymmetry in quality and minimum quality standards

A spatial price equilibrium model with information asymmetry in quality is developed in both static and dynamic versions. Producers at the supply markets are aware of the quality of their products, whereas consumers, located at the demand markets, are aware only of the average quality of the products that are shipped to their demand markets. Minimum quality standards are also captured in order to assess the impacts of such policy interventions. We establish qualitative results, in the form of existence, uniqueness, and stability analysis. An algorithm is proposed, along with a convergence proof. It is then utilized to compute solutions to a spectrum of spatial price equilibrium numerical examples in order to explore the impacts of information asymmetry under different scenarios. The numerical examples, which are of quite general functional forms, reveal that, as the number of supply markets increases, the “anonymizing” effect leads to a decrease in the average quality. On the other hand, as the number of demand markets increases, the pressure to improve quality increases, and the average quality increases. Finally, we demonstrate that, after the imposition of minimum quality standards, the average quality at the demand markets increases and the prices also increase.

Dynamics and Equilibria of Ecological Predator-Prey Networks as Nature’s Supply Chains

In this paper, we develop a dynamic network model of ecological food webs and prove that the set of stationary points of the projected dynamical system coincides with the set of solutions of a variational inequality governing the equilibrium of predator–prey networks. We also establish the equivalence between the ecological models and supply chain network equilibrium models and highlight the connections to spatial price equilibrium problems. We propose an algorithmic scheme, provide convergence results, and apply it to a food web drawn from a fisheries application.

Spatial price equilibrium and food webs: The economics of predator-prey networks

In this paper, we prove that the equilibrium of predator-prey networks is, in fact, a spatial price equilibrium. This result demonstrates the underlying economics of predator-prey relationships and interactions and provides a foundation for the formulation and analysis of complex food webs, which are natures supply chains, through the formalism of network equilibrium. Moreover, it rigorously links the equilibrium conditions of commodity networks in which a product is produced, transported, and consumed, with those of ecological networks in which prey are consumed by predators.

A junior course in engineering design and society

As part of an NSF grant, the College of Engineering at the University of Hartford is developing an interdisciplinary course in engineering practice. The purpose of the course is to introduce engineering students to the factors such as impact on society, political concerns, cultural concerns, that significantly affect their engineering design process, but are traditionally not part of a quantitative engineering design. A major focus of the course is communication. To be successful, an engineer must be able to communicate his/her results to a variety of interested individuals, stakeholders and bodies, both technical and non-technical. The paper discusses the course.

A Mean-Variance Disaster Relief Supply Chain Network Model for Risk Reduction with Stochastic Link Costs, Time Targets, and Demand Uncertainty

In this paper, we develop a mean-variance disaster relief supply chain network model with stochastic link costs and time targets for delivery of the relief supplies at the demand points, under demand uncertainty. The humanitarian organization seeks to minimize its expected total operational costs and the total risk in operations with an individual weight assigned to its valuation of the risk, as well as the minimization of expected costs of shortages and surpluses and tardiness penalties associated with the target time goals at the demand points. The risk is captured through the variance of the total operational costs, which is relevant to the reporting of the proper use of funds to stakeholders, including donors. The time goal targets associated with the demand points enable prioritization as to the timely delivery of relief supplies. The framework handles both the pre-positioning of relief supplies, whether local or nonlocal, as well as the procurement (local or nonlocal), transport, and distribution of supplies post-disaster. The time element is captured through link time completion functions as the relief supplies progress along paths in the supply chain network. Each path consists of a series of directed links, from the origin node, which represents the humanitarian organization, to the destination nodes, which are the demand points for the relief supplies. We propose an algorithm, which yields closed form expressions for the variables at each iteration, and demonstrate the efficacy of the framework through a series of illustrative numerical examples, in which trade-offs between local versus nonlocal procurement, post- and pre-disaster, are investigated. The numerical examples include a case study on hurricanes hitting Mexico.

Securing the Sustainability of Global Medical Nuclear Supply Chains Through Economic Cost Recovery, Risk Management, and Optimization

In this paper, we develop a new generalized network model for the optimization of the complex operations of medical nuclear supply chains in the case of the radioisotope molybdenum, with a focus on minimizing the total operational cost, the total waste cost, and the risk associated with this highly time-sensitive and perishable, but critical, product used in health-care diagnostics. Our model allows for the evaluation of transitioning the production and processing of the radioisotope from highly enriched uranium targets to low enriched uranium targets. A case study for North America demonstrates how our model and computational framework can be applied in practice.