Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to ...estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.
Power systems are critical infrastructure for reliable and secure electric energy delivery. Incidents are increasing, as unexpected multiple hazards ranging from natural disasters to cyberattacks ...threaten the security and functionality of society. Inspired by resilient ecosystems, this article presents a resilient network design approach with an ecological robustness (RECO)-oriented optimization to improve power systems' ability to maintain a secure operating state throughout unknown hazards. The approach uses RECO, a surprisal -based metric that captures key features of an ecosystem's resilient structure, as an objective to strategically design the electrical network. The approach enables solvability and practicality by introducing a stochastic-based candidate branch creation algorithm and a Taylor series expansion for relaxation of the RECO formulation. Finally, studies are conducted on the RECO-oriented approach using the IEEE 24 Bus RTS and the ACTIVSg200 systems. Results demonstrate improvement of the system's reliability under multiple hazards, network properties of robust structure and equally distributed power flows, and survivability against cascading failures. From the analysis, we observe that a more redundant network structure with equally distributed power flows benefits its resilience.
The recent COVID-19 pandemic revealed that healthcare networks must have a flexible and effective structure. In this study, we develop a viable healthcare network design for a pandemic using a ...multi-stage stochastic approach. We propose a multi-level network that includes health centers, computed tomography scan centers, hospitals, and clinics. Patients have conditions to returning to normal life or quarantining at home. Three objectives are defined: maximizing the probability of patient recovery, minimizing the costs of all centers in the network, and minimizing the Coronavirus death rate. We investigate a real case study in Iran to demonstrate the model’s applicability. Finally, we compare the healthcare supply chain network design in a pandemic with a normal situation to advise how the network can continue to remain viable.
•literature review aims at integration of reverse supply chain and waste management literature.•focus on strategic network design models in waste reverse supply chains.•potential of incorporating ...different stakeholders in waste reverse supply chain network design.•circular economy oriented practices challenge waste reverse supply chain network design.
In scientific literature two large, partly overlapping areas regarding the environmental and economical attractive removal of waste coexist: reverse logistics and waste management. Both fields study, among other topics, the flows of discarded products leaving the end consumer. This review takes an integrated point of view on reverse logistics and waste management and aims at a better integration. More specifically, it gives a concise but complete overview of the efforts already performed in the area of strategic network design in waste reverse supply chains by means of combinatorial optimization models. Its purpose is to guide interested readers and researchers directly to publications of their interest, and let them identify courses other than the well-worn paths. Among others, we explicitly refer to (1) the importance of environmental, social and performance indicators in multi-objective models, (2) the potential of incorporating the different waste reverse supply chain stakeholders into the network design model, (3) the consideration of future waste reverse supply chain developments like extended producer responsibility schemes and the circular economy and their challenges, and (4) better heuristics to deal with the increasingly complex strategic network design models.
During the COVID-19 pandemic, e-commerce retailers have had trouble satisfying the growing demand because of limited warehouse capacity constraints. Fortunately, an on-demand warehousing system has ...emerged as a new alternative to mitigate warehouse capacity issues. In recent years, several studies have focused on the supply chain problem considering on-demand warehousing. However, there is no study that deals simultaneously with inherent uncertainties and the property of commitment, which is the main advantage of on-demand warehousing. To fill these research gaps, this paper presents an e-commerce supply chain network design problem considering an on-demand warehousing and decisions for commitment periods. We propose the two-stage stochastic programming model that captures the inherent uncertainties to formulate the presented problem. We solve the proposed model utilizing sample average approximation combined with the Benders decomposition algorithm. Of particular note, we develop a method to generate effective initial cuts for improving the convergence speed of the Benders decomposition algorithm. Computational results show that the developed method could find an effective feasible solution within a reasonable computational time for problems of practical size. Furthermore, we show the significant cost-saving effects, based on experiment results, that occur when an on-demand warehousing system is used for designing supply chain networks.
Highly stretchable strain sensors based on conducting polymer hydrogel are rapidly emerging as a promising candidate toward diverse wearable skins and sensing devices for soft machines. However, due ...to the intrinsic limitations of low stretchability and large hysteresis, existing strain sensors cannot fully exploit their potential when used in wearable or robotic systems. Here, a conducting polymer hydrogel strain sensor exhibiting both ultimate strain (300%) and negligible hysteresis (<1.5%) is presented. This is achieved through a unique microphase semiseparated network design by compositing poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) nanofibers with poly(vinyl alcohol) (PVA) and facile fabrication by combining 3D printing and successive freeze‐thawing. The overall superior performances of the strain sensor including stretchability, linearity, cyclic stability, and robustness against mechanical twisting and pressing are systematically characterized. The integration and application of such strain sensor with electronic skins are further demonstrated to measure various physiological signals, identify hand gestures, enable a soft gripper for objection recognition, and remote control of an industrial robot. This work may offer both promising conducting polymer hydrogels with enhanced sensing functionalities and technical platforms toward stretchable electronic skins and intelligent robotic systems.
A conducting‐polymer hydrogel strain sensor is proposed with both high stretchability (300% strain) and ultralow hysteresis (<1.5%). The hydrogel‐based sensor harnesses a unique microphase semiseparated network to achieve enhanced sensing properties. The fabricated sensor can be applied as electronic skins to monitor physiological signals, enable a soft gripper for object recognition and remote control of an industrial robot.
•Matching supply chain design and production-ordering analysis in terms of ripple effect.•Post-disruption production-ordering instability in the supply chain has been observed and ...analysed.•Consequences of the production-ordering behavior during the disruption period are studied.•Formulation of revival control policy notion in the supply chain.•Insights on the recovery policies with consideration of post-disruption period.
We study production-ordering behaviour in a supply chain (SC) with disruption risks in recovery and post-disruption periods and the influence of severe disruptions on production and distribution network design. A real-life case-study of a disruption in a SC is considered and investigated with the help of discrete-event simulation blended with network optimisation in anyLogistix. Two novel findings are presented. First, disruption-driven changes in SC behaviour may result in backlog and delayed orders, the accumulation of which in the post-disruption period we call “disruption tails”. The transition of these residues into the post-disruption period causes post-disruption SC instability, resulting in further delivery delays and non-recovery of SC performance. Second, a smooth transition from the contingency policy through a special “revival policy” to normal operations mode partially mitigates the negative effects of disruption tails. The results show that isolated production and distribution network design optimisation can lead to severe decreases in performance in the event of SC disruptions. Contingent recovery policies need to be applied during the disruption period along with a revival policy in the post-disruption period to avoid disruption tails. These revival policies must be developed for the transition from the recovery to the disruption-free operations mode. A revival policy is meant to mitigate the negative impact of disruption tails and stabilise the ordering control policies and performance in the SC. Thus, recovery policies should not be limited to the disruption period only. They should also consider the post-disruption period and be included in SC design decisions. The revival policy should be included in the SC resilience framework.
Space-air-ground integrated network (SAGIN), as an integration of satellite systems, aerial networks, and terrestrial communications, has been becoming an emerging architecture and attracted ...intensive research interest during the past years. Besides bringing significant benefits for various practical services and applications, SAGIN is also facing many unprecedented challenges due to its specific characteristics, such as heterogeneity, self-organization, and time-variability. Compared to traditional ground or satellite networks, SAGIN is affected by the limited and unbalanced network resources in all three network segments, so that it is difficult to obtain the best performances for traffic delivery. Therefore, the system integration, protocol optimization, resource management, and allocation in SAGIN is of great significance. To the best of our knowledge, we are the first to present the state-of-the-art of the SAGIN since existing survey papers focused on either only one single network segment in space or air, or the integration of space-ground, neglecting the integration of all the three network segments. In light of this, we present in this paper a comprehensive review of recent research works concerning SAGIN from network design and resource allocation to performance analysis and optimization. After discussing several existing network architectures, we also point out some technology challenges and future directions.
In recent years, researchers have developed new methods to measure how transport decisions affect different groups of society. An example is the distribution of impacts (benefits and costs) from ...roadway investments, and the degree that the results are considered equitable (also called fair or just). Such decisions affect people’s ability to access services and activities, and therefore their economic opportunities and development. This study suggests ways of incorporating social equity measures in transportation network planning. It describes various equity impacts that can result from transportation planning decisions, discusses various social equity concepts and theories, reviews previous attempts to incorporate equity considerations into transport networks modeling, and suggests a framework for simultaneously optimizing network design and achieving social equity objectives. According to this framework, network design can be formulated using bi-level integer programming models corresponding to seven major social equity approaches along with the classical approach of “Total Travel Time Minimization.” An accessibility variable is used as the distributable benefit. This approach is more comprehensive and flexible than previous equity impact models. The proposed framework can be used to evaluate and optimize the equity impacts of various infrastructure investment decisions.
PDF
