Supply Network Management Research Articles

Online calibration of an integrated framework for information‐based evacuation operations

SummaryThis study seeks to online calibrate the parameters of aggregate evacuee behavior models used in a behavior‐consistent information‐based control module for determining information strategies for real‐time evacuation operations. It enables the deployment of an operational framework for mass evacuation that integrates three aspects underlying an evacuation operation: demand (evacuee behavior), supply (network management), and disaster characteristics. To attain behavior‐consistency, the control module factors evacuees' likely responses to the disseminated information in determining information‐based control strategies. Hence, the ability of the behavior models to predict evacuees' likely responses is critical to the effectiveness of traffic routing by information strategies. The mixed logit structure is used for the aggregate behavior models to accommodate the behavioral heterogeneity across the population. An online calibration problem is proposed to calibrate the random parameters in the behavior models by using the least square estimator to minimize the gap between the predicted network flows and unfolding traffic dynamics. Background traffic, an important but rarely studied issue for modeling evacuation traffic, is also accounted for in the proposed problem. Numerical experiments are conducted to illustrate the importance of the calibration problem for addressing the system consistency issues and integrating the demand, supply, and disaster characteristics for more efficient evacuation operations. Copyright © 2016 John Wiley & Sons, Ltd.

Visual analytics for supply network management: System design and evaluation

We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.

Developing a resilient supply chain strategy during ‘boom’ and ‘bust’

Supply chain resilience is often perceived as highly desirable, as it increases a firm’s readiness in dealing with risks that can emerge from the customers’ side, the suppliers’ side, the internal processes adopted and the supply chain integration mechanisms employed. However, though practitioners responsible for the design and management of supply networks often see resilience as highly desirable, they also see the direct trade-off being cost. An in-depth qualitative single case is presented in this study, using an iterative cycle between theory and practice to delve into the experiences of the case company and various concepts from the literature. A framework for the development and implementation of a resilient supply chain strategy is proposed, which illustrates the relevance of various management paradigms (robustness, agility, leanness and flexibility) in increasing a company’s ability to deal with disturbances emerging from its supply chain. The paper advances theory and closes some of the gaps in the literature with regard to the ways certain management paradigms could be combined in practice in order to develop a supply chain resilience strategy.

A Cloud Platform to support Collaboration in Supply Networks

<div><p class="TtuloAbstract">Collaboration is a trend in supply networks management, based on the jointly planning, coordination and integration of processes, participating all network entities. Due to the current characteristics of uncertainty in the markets and economic crisis, there is a need to encourage collaboration tools to reduce costs and increase trust and accountability to market requirements. This study presents an overview of the research carried out in the H2020 European Project: Cloud Collaborative Manufacturing Networks (C2NET), which is directed towards the development a cloud platform that consist of, optimization tools, collaboration tools to support and agile management of the network. The collaborative cloud platform allows to collect real time information coming from real-world resources and considering all the actors involved in the process. The collaborative cloud provides real time data gathered from the entire network partners in order to improve their decision-making processes.</p></div>

Responsible buying practices in supply risk management

Supply management is responsible for the management of a firm's supply network and risks arising from the supply base. Thus, defined principles and practices related to responsibility of purchasing are highly critical. The aim of this paper is to discuss the role of responsible buying practices in supply risk management. This is examined by utilising quantitative survey data collected in Finland. The results show that responsible buying practices correlate positively with supply risk management. However, there are differences in terms of risk type. The empirical data showed that the more attention paid to corporate social responsibility (CSR), third-party and delivery risks, the higher the usage of responsible buying practices. Furthermore, it was found that country risk does not correlate with CSR risk and third-party risk, and risks vary according to the industry and nature of business.

M724 最適化手法を用いたエネルギー供給ネットワークの運用マネジメント : 温水融通時の運用計画再立案効果(GS10,12 製造・エネルギー供給の最適化,修士研究発表セッション)

M724 最適化手法を用いたエネルギー供給ネットワークの運用マネジメント : 温水融通時の運用計画再立案効果(GS10,12 製造・エネルギー供給の最適化,修士研究発表セッション)

Research on Construct of Energy Management Platform Based on Marketing and Distribution Integrated System

Marketing and Distribution Integrated System is based on GIS systems, and a unified information model of power grid equipment, basic data and topology-based systems, the use of high-tech information technology, application management and distribution line losses quarter field of network construction planning, customer outage management and other integrated information platform. Energy management system implementation ultimate goal is to achieve through intelligent system integration of existing systems be saving energy consumption and improved. In automation technology and IT based on the establishment of energy management systems, based on objective data, metallurgical, chemical, thermal, power plants and other energy consuming enterprises, energy saving most fundamental way to implement. The foundation and core of this system is that the data distribution network GIS platform, integrated measurement automation, distribution network of production, distribution network planning, distribution network automation, distribution network engineering, marketing and other systems supporting the management and reliability of power supply and distribution network planning decisions Camp with information query formulated meter reading routes and other services.

The vulnerability of the US food system to climate change

The climate change vulnerability of a food system is a function of the exposure of the system to specific climate effects, the sensitivity of the system to those effects, and the capacity of the system adapt to those effects in order to maintain system integrity. A synthesis of recent literature conducted to explore the vulnerability of the US food system to climate change suggests that the interaction between regional climate change effects and the geographic specialization and concentration of agricultural production in the USA increases the vulnerability of the US food system to climate change. Vegetable and fruit production in the Pacific states are particularly sensitive to reduced water supplies, warmer winters, and more variable spring weather. Grain production in the Great Plains and the Midwest is sensitive to more variable weather, warmer winters, heat wave, and hot summer nights and flooding caused by more frequent heavy rains. The concentration of beef, pork, and poultry production in confined animal feeding operations located in the southern Great Plains and the Southeast is particularly sensitive to increased frequency and intensity of extreme weather and interruptions in feed, water, and power supplies associated with interactions between land, water, and energy use that amplify climate change effects. There is evidence that climate change is already causing disruptions throughout the US food system. Farmers and ranchers in the US report that increased weather variability and more frequent and intense weather extremes have increased the costs and complexity of food production. Businesses operating in the US agricultural supply, processing, distribution, and retailing sectors are actively managing supply networks to reduce disruptions associated with climate change effects. Food systems that rely on external or distant resources and specialized production, supply, and marketing chains appear to be particularly vulnerable to global environmental change. These characteristics, widely recognized as critical challenges to the sustainability of the US food system, take on new importance as barriers to climate resilience.

Network diversity and supplier network performance: a case study

Through combining the portfolio theory and business network theory, the paper tries to analyse the supplier network performance from network ties, network structure and node activity and investigates which is the factor affecting supplier network performance mostly in network ties, network structure and node activity respectively. The results show that information sharing and staff exchanging in network ties, business proportion in network structure, ranking of Midea in vendors' offering companies and strength of technical cooperation in node activity are the most important factors affecting the performance of Midea air-conditioning division's supplier network. The implications of these findings for supplier network management related with focal company's benefits are discussed and limitations and recommendations for future research are also presented.

Water Supply Network Monitoring Based on Demand Reverse Deduction (DRD) Technology

DRD technology is a new method to calculate the node water demand based on the monitoring node pressure of the water supply network. This method is able to acquire the water consumption in every node of the monitoring area. Therefore, no flow meter is needed to install on the main pipes. This paper describes the technical details of DRD application and the design of monitoring platform based on wireless sensor network (WSN). A case study is carried out in an actual water supply network and the result shows this method is accurate enough to provide decision support for water supply network management.

Implementing an evolutionary algorithm for locating container yards of a 3PL provider

Defining the facility location is considered as a strategic decision in the context of the supply network management. Often, this decision is made based on minimum cost or best service criteria. However, most of the time these criteria are taken into account separately because the inherent complexity of the multi-objective optimization problems. This study shows the application of the multi-objective evolutionary algorithm known as NSGAII in a real situation faced by a logistics operator in Colombia in order to evaluate different alternatives of distribution for this company.

A genetic algorithm for demand pattern and leakage estimation in a water distribution network

Research Article| June 25 2014 A genetic algorithm for demand pattern and leakage estimation in a water distribution network Armando Di Nardo; Armando Di Nardo 1Department of Civil Engineering, Design, Building and Environment, Second University of Naples, via Roma, 29, 81031 Aversa (CE), Italy Search for other works by this author on: This Site PubMed Google Scholar Michele Di Natale; Michele Di Natale 1Department of Civil Engineering, Design, Building and Environment, Second University of Naples, via Roma, 29, 81031 Aversa (CE), Italy Search for other works by this author on: This Site PubMed Google Scholar Corrado Gisonni; Corrado Gisonni 1Department of Civil Engineering, Design, Building and Environment, Second University of Naples, via Roma, 29, 81031 Aversa (CE), Italy Search for other works by this author on: This Site PubMed Google Scholar Michele Iervolino Michele Iervolino 1Department of Civil Engineering, Design, Building and Environment, Second University of Naples, via Roma, 29, 81031 Aversa (CE), Italy E-mail: michele.iervolino@unina2.it Search for other works by this author on: This Site PubMed Google Scholar Journal of Water Supply: Research and Technology-Aqua (2015) 64 (1): 35–46. https://doi.org/10.2166/aqua.2014.004 Article history Received: January 09 2014 Accepted: May 21 2014 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Cite Icon Cite Permissions Search Site Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThis Journal Search Advanced Search Citation Armando Di Nardo, Michele Di Natale, Corrado Gisonni, Michele Iervolino; A genetic algorithm for demand pattern and leakage estimation in a water distribution network. Journal of Water Supply: Research and Technology-Aqua 1 February 2015; 64 (1): 35–46. doi: https://doi.org/10.2166/aqua.2014.004 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex The sustainable management of water supply networks requires the control of physical pipe leakages, such as those due to junction obsolescence or pipe creeping. These leakages usually increase with the operating pressure, and their discharge is commonly assumed to scale with the power of the pressure. The same functional form is also employed to evaluate leakage occurring in the portion of the network downstream a node. The parameters involved in these relationships may be estimated from field experimental data. However, a sensible fluctuation in their values is observed, and therefore the definition of a suitable leakage law represents a major source of uncertainty in water network modeling. In the present paper, the estimation of the leakage law parameters is carried out simultaneously to the hourly demand pattern. To this aim, a hydraulic network model coupled to a genetic algorithm is employed to minimize the deviation between predicted and measured time series of pressure and flow at a small number of sites of the network. A field test case is analyzed to show the effectiveness of the proposed procedure. demand models, genetic algorithms, leakages, optimization, water distribution networks © IWA Publishing 2015 You do not currently have access to this content.

Investigating the demand propagation in EOQ supply networks using a probabilistic model

In this paper, we introduce a new demand probabilistic approach, named M.DPA.eoq (Montanari Demand Probabilistic Approach in economic order quantity [EOQ] scenario), for predicting the demand seen by an upper tier echelon (e.g. a distribution centre) of a supply network, serving several lower tier echelons operating according to an EOQ reorder policy. The M.DPA.eoq is based on an analytic approach, by which we derive the distribution of the demand seen by the upper tier echelon of the supply network. The approach has been designed to be very simple, so as to gain in pedagogical value. The simplicity and ease of application of this approach are confirmed by the possibility of exploiting general purpose software, such as Microsoft ExcelTM, to implement and validate it. Moreover, the M.DPA.eoq has potential to be directly exploited by practitioners, such as supply network managers, to estimate the distribution of the demand the upper tier echelon will face under a defined network structure. Students and researchers could also benefit from such a model, given its ease of understanding and usage. With the purpose of showing its potential usefulness in real cases, we discuss two practical implications of the M.DPA.eoq, referring to the use of its results for: (1) computing the bullwhip effect of the network; and (2) analysing the impact of each retail store on the variance of the demand seen by the upper tier echelon.

Critical points: interactions between on-farm irrigation systems and water distribution network

In this work, a new model useful to analyze interactions between the on-farm irrigation system supplied by critical points and the water supply network management was developed. The model evaluates the impacts of changes in the pressure head and demand simultaneity (number of open hydrants at a given time) on the irrigation system and evaluates emitter discharge and uniformity. It also estimates the potential reductions in crop yield due to decreased emission uniformity. The methodology is applied in the Bembezar Irrigation District (Southern Spain). Results show that the additional cost required for providing maximum pressure to the critical field does not offset the increase in crop yield. Hence, an increment from 91.7 to 92.1 % in yield in the critical field would represent increases in energy consumption from 0.15 to 0.17 kWh m−3 of water. Also, the unit energy cost could be reduced by up to 0.11 kWh m−3 without implying significant reductions in crop yield. The importance of a good selection of emitters in the critical fields (fields that are supplied by the critical hydrants) was also evaluated.

Improved Real-time Monitoring and Control of Water Supply Networks by Use of Graph Decomposition

In this paper, the concept of graph decomposition is used for simplification and enhancement of solution algorithms for different problems related to water supply network security and management. Three examples including sensor placement, source identification and decision support for response actions are presented. The decomposition concept can be used as general framework for adaptive modeling. Based on one comprehensive all pipe model of the entire supply system, the most appropriate level of accuracy can be chosen. Unlike conventional network aggregations and simplification algorithms, the proposed model simplifications do not have the problem of losing the original information. The method is suited for being used within a real-time environment where calculation time is one of the most important requirements for practical applicability.

An integrated approach based-structural modeling for risk prioritization in supply network management

Supply networks are complex and suffer always from various risks. An effective supply chain management requires suitable strategies to mitigate them. In previous literature, there has been a range of research into risk in firms but little in supply networks. This can be explained due to the huge number of risk variables and their direct and indirect interrelations that may suffer all supply chain partners (firms). Therefore, for better risk mitigation, a risk prioritization step is vital. To this end, the purpose of this paper is to propose a new integrated approach based on two structural modeling tools. Firstly, interpretive structural modeling has been used to present a hierarchical model showing the interrelationships between the risk sources. Secondly, MICMAC analysis has been used to quantify and classify the risk variables based on their mutual influence and dependence. The objective is to ascertain the key risk variables and theirs relationships. These prioritized risk variables provide a useful tool to supply network managers to focus on those key variables that are most essential for effective risk management strategies. A real case study in food industry is provided in order to illustrate the application of the proposed approach. The findings may be useful to the practitioners in risk management and may also interest academicians, since the method used here can be applied in other areas of industrial management as well.

A decision management tool: modelling the order fulfilment process by multi-agent systems

This paper describes an agent-based framework for modelling and simulating different processes taking place in supply networks, resulting in a supply network simulator. The framework is composed of reusable elements (agents and objects) allowing to model real-scale supply chains, which often involves a high number of different enterprises and products, and many different structures are possible. Each enterprise in the model can be customised with different policies and parameters for the different business functions. The framework is implemented using Java Swarm. The simulation platform, called Sistemas COoperativos para la Programacion y Ejecucion de pedidos (SCOPE), has been validated contrasting our results with three different methodologies described in the literature by three relevant authors in the supply network management topic. SCOPE is a very useful tool for supply network managers, allowing them to understand how their current system works, to calculate global performances, and to fine-tune the current system by simulation (changing parameters, management policies, adding or deleting new enterprises, etc.).

Control of supply networks by robust optimal control and using observers

The control strategy to organize the flow of goods is extremely important in managing supply networks. Handling of uncertainty, e.g. customer demand, is often a considerable challenge. We introduce methods of constrained robust optimal control, a technique from control theory, to compute the explicit control strategy for small-sized demand-driven discrete-time controlled dynamical systems with uncertainties. This allows us to avoid any assumptions about the form of the policy a priori. We aim to show the applicability of the methods, instead of finding innovative policies as the resulting policies are well known. Another control problem arises when control actions depend on the information of multiple states and these states are not (completely) known, e.g. due to communication issues. We use observers, another technique from the control theory, to derive the required state information based on the in- and output. By means of an example, it is shown that by using these observers, the control policy can be perfectly utilized and no longer depends on communication.

Transforming humanitarian logistics: the journey to supply network management

Transforming humanitarian logistics: the journey to supply network management

What Skills and Attributes are Desired of Australian Supply Network Managers?

Against a background of increasing business volatility that will impact on the design and operation of supply networks (SN), this research describes the outcome of a survey of 210 Australian business executives who were invited to indicate the skills and attributes that they perceive to be important in SN managers. The research found that, whilst the notion of 'agility' is increasingly found in the literature relating to SN management, there is only relatively limited discussion of what such agility entails and, hence, what skills and attributes might be required by those managing such networks. From a practitioner perspective, however, the areas of problem solving, inter-personal and business management skills are more highly rated that those related to the functions of logistics/ SN management. This has clear implications for the design of education courses in this field as these may need to be more clearly focussed on developing an improved understanding of the theory and practice of modern management as it relates supply networks, and less on their operation.