Unraveling the Design Principle for Motif Organization in Signaling Networks

Cellular signaling networks display complex architecture. Defining the design principle of this architecture is crucial for our understanding of various biological processes. Using a mathematical model for three-node feed-forward loops, we identify that the organization of motifs in specific manner within the network serves as an important regulator of signal processing. Further, incorporating a systemic stochastic perturbation to the model we could propose a possible design principle, for higher-order organization of motifs into larger networks in order to achieve specific biological output. The design principle was then verified in a large, complex human cancer signaling network. Further analysis permitted us to classify signaling nodes of the network into robust and vulnerable nodes as a result of higher order motif organization. We show that distribution of these nodes within the network at strategic locations then provides for the range of features displayed by the signaling network

Designing Electricity Distribution Networks: The Impact of Demand Coincidence

With the global effort to reduce carbon emissions, clean technologies such as electric vehicles and heat pumps are increasingly introduced into electricity distribution networks. These technologies considerably increase electricity flows and can lead to more coincident electricity demand. In this paper, we analyze how such increases in demand coincidence impact future distribution network investments. For this purpose, we develop a novel model for designing electricity distribution networks, called the distribution network reconfiguration problem with line-specific demand coincidence (DNRP-LSDC). Our analysis is two-fold: (1) We apply our model to a large sample of real-world networks from a Swiss distribution network operator. We find that a high demand coincidence due to, for example, a large-scale uptake of electric vehicles, requires a substantial amount of new network line construction and increases average network cost by 84 % in comparison to the status quo. (2) We use a set of synthetic networks to isolate the effect of specific network characteristics. Here, we show that high coincidence has a more detrimental effect on large networks and on networks with low geographic consumer densities, as present in, e. g., rural areas. We also show that expansion measures are robust to variations in the cost parameters. Our results demonstrate the necessity of designing policies and operational protocols that reduce demand coincidence. Moreover, our findings show that operators of distribution networks must consider the demand coincidence of new electricity uses and adapt investment budgets accordingly. Here, our solution algorithms for the DNRP-LSDC problem can support operators of distribution networks in strategic and operational network design tasks.Comment: Accepted manuscript, to appear in European Journal of Operational Research (EJOR

Optimal scope of supply chain network & operations design

The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are significant and that has attracted considerable research attention since the late 1990s. This doctoral thesis focuses on developing manageable and realistic optimization models for solving four contemporary and interrelated supply chain network and operations design problems. Each requires an integrated decision-making approach for advancing supply chain effectiveness and efficiency. The first model formulates the strategic robust downsizing of a global supply chain network, which requires an integrated decision-making on resource allocation and network reconfiguration, given certain financial constraints. The second model also looks at the strategic supply chain downsizing problem but extends the first model to include product portfolio selection as a downsizing decision. The third model concerns the redesign of a warranty distribution network, which requires an integrated decision-making on strategic network redesign and tactical recovery process redesign. The fourth model simultaneously determines the operational-level decisions on job assignment and process sequence in order to improve the total throughput of a production facility unit

Cascading Effects of Fuel Network Interdiction

This thesis develops the Fuel Interdiction and Resulting Cascading Effects (FI&RCE) model. The study details the development and experimental testing of a framework for assessing the interdiction of a refined petroleum production and distribution network. FI&RCE uses a maximum flow mathematical programming formulation that models the transit of fuels from points of importation and refinement through a polyduct distribution network for delivery across a range of end user locations. The automated model accommodates networks of varying size and complexity. FI&RCE allows for parameters and factor settings that enable robust experimentation through implementation in MATLAB 2014 and the commercial solver CPLEX (Version 12.5). Experimental design allows the investigation of interdiction or disruption on supply and network infrastructure locations in order to support the strategic analytical needs of the user. Given a target set, FI&RCE provides measured responses for the resulting fuel availability and a valuation of economic loss. The value of economic loss feeds a Leontief based input-output model that assesses the cascading effects in the studied economy by implementing a mathematical program that optimizes the remaining industrial outputs. FI&RCE demonstrates a framework to investigate the military and cascading effects of a fuel interdiction campaign plan using a realistic case study

Intelligent management experience on efficient electric power system

Electric power system is one of the most critical and strategic infrastructures of industrial societies. Nowadays, it is necessary the modernization and automation of the electric power grid to increase energy efficiency, reduce emissions, and transit to renewable energy. Power utilities face the challenge of using information and communication networks more effectively to manage the demand, generation, transmission, and distribution of their commodity services. Communication network constitutes the core of the electric system automation applications, the design of a cost-effective, and reliable network architecture is crucial. To resolve this difficulty in this work we study the integration of advanced artificial intelligence technology into existing network management system. This work focuses on an intelligent framework and a language for formalizing knowledge management descriptions and combining them with existing OSI management model. We have normalized the knowledge management base necessary to manage the current resources in the telecommunication networks. Intelligent agents learn the normal behaviour of each measurement variable and combine the intelligent knowledge for the management of the network resources. We present an analysis of corporate network management requirements and technologies, together with our implementation experience with the development of an integrated management system for a company network

A Dynamic Adaptive Approach for Water Distribution Network Design

This is the author accepted manuscript. The final version is available from American Society of Civil Engineers via the DOI in this record In the face of a highly uncertain future, there is a need for water utilities to develop structured approaches for the long-term strategic design of water distribution networks (WDNs). A new conceptual framework for developing an integrative approach based on a multicriteria decision analysis (MCDA), embracing an optimization model to size flexible alternatives, is proposed. The flexible solutions are evaluated through MCDA for all the criteria (investment costs, carbon emissions, resilience, and reliability of WDNs) across all the scenarios generated for the sake of robustness and will help to adapt WDNs to changing conditions over a long planning horizon, divided into phases. The alternatives are ranked through two different MCDA methods, Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), so that decision makers will have more comprehensive information for analyzing highly ranked design solutions and after the first phase, solutions for the other phases can be reassessed by the same dynamic adaptive framework

A Bi-Objective Programming Model for Reliable Supply Chain Network Design Under Facility Disruption

Supply chain networks generally are composed of four main entity types: supplier, production centers, distribution centers and demand zones that consist of facilities whose activities involve the transformation of raw material into finished products that are later delivered from the suppliers to the end customers. Supply chain network design as the most important strategic decision in supply chain management plays an important role in the overall environmental and economic performance of the supply chain. The nature and complexity of today’s supply chains network make them vulnerable to various risks. One of the most important risks is disruption risk. Disruptions are costly and can be caused by internal or external sources to the supply chain, thus it is crucial that managers take appropriate measures of responses to reduce its negative effects. A recovery time of disrupted facilities and return it to the normal condition can be an important factor for members of the supply chain. In this paper, a bi-objective model is developed for reliable supply chain network design under facility disruption. To solve this model, we have applied two approaches, i.e., ε constraint method as an exact method and non- dominated sorting genetic algorithm (NSGAII) as a meta-heuristic method

Generic models for the integrated design of domestic and global supply chain networks with remanufacturing

This research focuses on the modeling of strategic supply chain network design. Several comprehensive mixed-integer-programming models are developed for the strategic integrated design of domestic and global supply chain networks with remanufacturing capacity. The models allow simultaneous determination of supplier selection, manufacturing and distribution facility selection and allocation, production quantities, transportation flows, reverse distribution facility selection, and disassembly plant allocation. Additionally, our models incorporate bill of material (BOM) both in the manufacturing process and in disassembly process. Management policies are also considered in the model formulation so that specific management choices, such as multi- sourcing strategy or single sourcing strategy, can be fulfilled in the strategic supply chain network design. Global factors considered in the model include currency exchange rates, transfer prices, allocation of transportation costs, local content requirements, local income taxes, and tariffs. The models are verified by medium-sized numerical examples. Compared to previous literature, the proposed models have two distinctive features. First, the corresponding integrated logistics problem of a global supply chain is formulated with a generalized mathematical form, and thus is not limited to applications for specific industries. Such a methodological measure is rare in previous literature, and has exhibited its potential advantages in addressing complicated global supply chain problems. Second, remanufacturing factors oriented from the enforcement of corresponding governmental regulations for environmental protection are considered in the proposed model. Thus, the corresponding effects may help to determine solution alternatives to improve the performance of a global supply chain with remanufacturing capacit

Social Justice Documentary: Designing for Impact

Explores current methodologies for assessing social issue documentary films by combining strategic design and evaluation of multiplatform outreach and impact, including documentaries' role in network- and field-building. Includes six case studies

The strategic importance of supply chains and the RFID radio data identification system

Purpose: The paper presents the issues related to the process of supply chain management. It presents the essence and classification of supply chains and the interpretation of global supply network management. Design/Methodology/Approach: Using systems theory as a basis, a RFID utilization and outcome(s) performance model was developed from the literature. The study uses surveys conducted among twenty companies in the 2016-2017 research year. Enterprises that use RFID technologies in the supply chain were analyzed. Findings: The Findings indicate that application of RFID technology leads to improved manufacturing efficiency and manufacturing effectiveness, while improvement in efficiency lead directly to improved organizational performance, and improvements in effectiveness lead directly to improved supply chain performance. Practical Implications: Certain policy implications and obligations accrue are companies that use RFID technology in their supply order to manage the company more efficiently. Originality/Value: The publication presents the results of research carried out in enterprises using the new RFID system as a modern technique of supporting supply chain management to increase the efficiency of cooperation throughout the entire supply chain.peer-reviewe