Collaborative Models for Supply Networks Coordination and Healthcare Consolidation

This work discusses the collaboration framework among different members of two complex systems: supply networks and consolidated healthcare systems. Although existing literature advocates the notion of strategic partnership/cooperation in both supply networks and healthcare systems, there is a dearth of studies quantitatively analyzing the scope of cooperation among the members and its benefit on the global performance. Hence, the first part of this dissertation discusses about two-echelon supply networks and studies the coordination of buyers and suppliers for multi-period procurement process. Viewing the issue from the same angel, the second part studies the coordination framework of hospitals for consolidated healthcare service delivery. Realizing the dynamic nature of information flow and the conflicting objectives of members in supply networks, a two-tier coordination mechanism among buyers and suppliers is modeled. The process begins with the intelligent matching of buyers and suppliers based on the similarity of users profiles. Then, a coordination mechanism for long-term agreements among buyers and suppliers is proposed. The proposed mechanism introduces the importance of strategic buyers for suppliers in modeling and decision making process. To enhance the network utilization, we examine a further collaboration among suppliers where cooperation incurs both cost and benefit. Coalitional game theory is utilized to model suppliers\u27 coalition formation. The efficiency of the proposed approaches is evaluated through simulation studies. We then revisit the common issue, the co-existence of partnership and conflict objectives of members, for consolidated healthcare systems and study the coordination of hospitals such that there is a central referral system to facilitate patients transfer. We consider three main players including physicians, hospitals managers, and the referral system. As a consequence, the interaction within these players will shape the coordinating scheme to improve the overall system performance. To come up with the incentive scheme for physicians and aligning hospitals activities, we define a multi-objective mathematical model and obtain optimal transfer pattern. Using optimal solutions as a baseline, a cooperative game between physicians and the central referral system is defined to coordinate decisions toward system optimality. The efficiency of the proposed approach is examined via a case study

The State-of-the-Art Survey on Optimization Methods for Cyber-physical Networks

Cyber-Physical Systems (CPS) are increasingly complex and frequently integrated into modern societies via critical infrastructure systems, products, and services. Consequently, there is a need for reliable functionality of these complex systems under various scenarios, from physical failures due to aging, through to cyber attacks. Indeed, the development of effective strategies to restore disrupted infrastructure systems continues to be a major challenge. Hitherto, there have been an increasing number of papers evaluating cyber-physical infrastructures, yet a comprehensive review focusing on mathematical modeling and different optimization methods is still lacking. Thus, this review paper appraises the literature on optimization techniques for CPS facing disruption, to synthesize key findings on the current methods in this domain. A total of 108 relevant research papers are reviewed following an extensive assessment of all major scientific databases. The main mathematical modeling practices and optimization methods are identified for both deterministic and stochastic formulations, categorizing them based on the solution approach (exact, heuristic, meta-heuristic), objective function, and network size. We also perform keyword clustering and bibliographic coupling analyses to summarize the current research trends. Future research needs in terms of the scalability of optimization algorithms are discussed. Overall, there is a need to shift towards more scalable optimization solution algorithms, empowered by data-driven methods and machine learning, to provide reliable decision-support systems for decision-makers and practitioners

Coupled computational fluid dynamics-response surface methodology to optimize direct methanol fuel cell performance for greener energy generation

Optimization of operational parameters is vital for improving the performance of direct methanol fuel cells. To investigate the effects of these parameters on the power density, the experiments were performed using an experimental setup to yield the highest performance. In this regard, response surface methodology (RSM) was applied to select the proper combination of operating variables such as cell temperature, methanol concentration, and oxygen flow rate. Furthermore, a computational fluid dynamics (CFD) model of DMFC flow field plates, including two parallel-serpentine channels with circular bends were conducted using the finite element method at the optimum operating conditions, which obtained by applying RSM. The developed model solves the conservation of charge, mass, momentum, and species (methanol, water, and oxygen) transport equations. The performance tests based on RSM gave the optimum operating conditions as a cell temperature of 70 degrees C, methanol concentration of 1 M, and an oxygen flow rate of 300 ml/min. The mathematical model in the optimal operating conditions showed that the polarization curve obtained from the modeling study is in good agreement with the experimental data. Also, the concentration distributions of methanol and oxygen at the optimum operating conditions were predicted by the CFD model. (C) 2020 Elsevier Ltd. All rights reserved

Vitrification affects the expression of matrix metalloproteinases and their tissue inhibitors of mouse ovarian tissue

Background: One of the most major obstacles of ovarian tissue vitrification is suboptimal developmental competence of follicles. Matrix metalloproteinases 2 (MMP-2) and 9 (MMP-9) and their tissue inhibitors TIMP-1 and TIMP-2 are involved in the remodeling of the extracellular matrix in the ovaries. Objective: This study aimed to evaluate the expression of MMP-2, MMP-9, TIMP-1, and TIMP-2 genes in the preantral follicles derived from vitrified mouse ovaries. Materials and Methods: In this experimental study, the gene expression of MMP-2, MMP-9, TIMP-1, and TIMP-2 in the isolated preantral follicles derived from fresh and vitrified ovaries of 14-16 days old female mice through real time qRT-PCR was evaluated. Developmental parameters, including survival rate, growth, antrum formation and metaphase II oocytes were also analyzed. Results: The developmental parameters of fresh preantral follicles were significantly higher than vitrified preantral follicles. The TIMP-1 and MMP-9 expression levels showed no differences between fresh and vitrified preantral follicles (p=0.22, p=0.11 respectively). By contrast, TIMP-2 expression significantly decreased (p=0.00) and MMP-2 expression increased significantly (p=0.00) in vitrified preantral follicles compared with to fresh ones. Conclusion: Changes in expression of MMP-2 and TIMP-2 after ovarian tissues vitrification is partially correlated with decrease in follicle development