Optimal bidding in auctions from a game theory perspective

Winner determination of loss-averse buyers with incomplete information in multiattribute reverse auctions for clean energy device procurement

A two-stage stochastic winner determination model integrating a hybrid mitigation strategy for transportation service procurement auctions

In this paper, resource allocation (RA) problem in heterogeneous Software Defined Network (SDN) with infrastructure sharing platform among multiple network service providers (NSPs) is studied. The considered problem is modeled as a reverse combinatorial auction (R-CA) game, which takes competitiveness and fairness of different NSPs into account. The heterogeneous RA associated with personal QoS requirement problem is optimized by maximizing the social welfare, which is demonstrated to be total system throughput. By exploiting the properties of iterative programming, the resulting non-convex Winner Determination Problem (WDP) is transformed into an equivalent convex optimization problem. The proposed R-CA game is strategy- proof and proved to be with low computational complexity. Simulation results illustrate that with SDN controller sharing environment, the proposed iterative ascending price Vickrey (IA-PV) algorithm converges fast and can obtain nearly optimal system throughput. It is also demonstrated to be robust with density changing, enable higher fairness and ensure individual profit among different NSPs. With the fairness guaranteed, this infrastructure sharing SDN platform can attract more NSPs to participate, in order to achieve more profit and cost reduction.

Reverse Combinatorial Auction Based Resource Allocation in Heterogeneous Software Defined Network with Infrastructure Sharing

Truthfulness with value-maximizing bidders: On the limits of approximation in combinatorial markets☆

A Lagrangian approach to the winner determination problem in iterative combinatorial reverse auctions

Assessment of water demand reliability using SWAT and RIBASIM models with respect to climate change and operational water projects

Optimal pricing in iterative flexible combinatorial procurement auctions

This review focuses on vaccine distribution and allocation in the context of the current COVID-19 pandemic. The implications discussed are in the areas of equity in vaccine distribution and allocation (at a national level as well as worldwide), vaccine hesitancy, game-theoretic modeling to guide decision-making and policy-making at a governmental level, distribution and allocation barriers (in particular in low-income countries), and operations research (OR) mathematical models to plan and execute vaccine distribution and allocation. To conduct this review, we adopt a novel methodology that consists of three phases. The first phase deploys a bibliometric analysis; the second phase concentrates on a network analysis; and the last phase proposes a refined literature review based on the results obtained by the previous two phases. The quantitative techniques utilized to conduct the first two phases allow describing the evolution of the research in this area and its potential ramifications in future. In conclusion, we underscore the significance of operations research (OR)/management science (MS) research in addressing numerous challenges and trade-offs connected to the current pandemic and its strategic impact in future research. 

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Vaccine Allocation and Distribution: A Review with a Focus on Quantitative Methodologies and Application to Equity, Hesitancy, and COVID-19 Pandemic

Background: The ramifications of climate change are rampant: All stakeholders must act effectively and swiftly. Unsustainable and increased urbanization adds additional strain on combatting environmental degradation. Since the last decade, urban distribution centers (UDCs) have emerged in response to the steep rise in urban freight transportation and its negative impact on city congestion and air quality. Methods: In this paper, we conduct a comprehensive review of the performance of UDCs and investigate its alignment with the corporate governance (CG) and corporate social responsibility (CSR) initiatives, including the shareholders’ governance strategies and policies, as well as environmental, social, and economic measures. Our systematic literature review consists of multiple phases: In the first one, we utilize bibliometric tools to implement a quantitative analysis of the extant literature. Next, a cluster-based network analysis complements this analysis to describe the evolution of research in this area. Results: Our descriptive analysis categorizes existing research on UDCs based on CG- and CSR-compliant themes. We classify pertinent peer-reviewed articles into topical clusters and offer research opportunities related to improving the performance of UDCs. Conclusions: This study aims to stimulate further scholarly inquiry into sustainable city logistics and provides a knowledge-based guide for academicians and practitioners, logistics service providers, policymakers, and customers.

/pdf/toward-greening-city-logistics-a-systematic-review-on-2g9sbwhj.pdf

Bahareh Mansouri

Papers

A Lagrangian approach to the winner determination problem in iterative combinatorial reverse auctions

Assessment of water demand reliability using SWAT and RIBASIM models with respect to climate change and operational water projects

Optimal pricing in iterative flexible combinatorial procurement auctions

Vaccine Allocation and Distribution: A Review with a Focus on Quantitative Methodologies and Application to Equity, Hesitancy, and COVID-19 Pandemic

Toward Greening City Logistics: A Systematic Review on Corporate Governance and Social Responsibility in Managing Urban Distribution Centers