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1 – 10 of over 2000Pham Duc Tai, Krit Jinawat and Jirachai Buddhakulsomsiri
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a…
Abstract
Purpose
Distribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.
Design/methodology/approach
The problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.
Findings
For the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.
Originality/value
The proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.
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Barbara Da Roit and Maurizio Busacca
The paper aims to analyse the meaning and extension of discretionary power of social service professionals within network-based interventions.
Abstract
Purpose
The paper aims to analyse the meaning and extension of discretionary power of social service professionals within network-based interventions.
Design/methodology/approach
Empirically, the paper is based on a case study of a network-based policy involving private and public organisations in the Northeast of Italy (Province of Trento).
Findings
The paper identifies netocracy as a social policy logic distinct from bureaucracy and professionalism. What legitimises netocracy is neither authority nor expertise but cooperation, the activation of connections and involvement, considered “good” per se. In this framework, professionalism and discretion acquire new and problematic meanings compared to street-level bureaucracy processes.
Research limitations/implications
Based on a case study, the research results cannot be generalised but pave the way to further comparative investigations.
Practical implications
The paper reveals that the position of professionals in netocracy is to some extent trickier than that in a bureaucracy because netocracy seems to have the power to encapsulate them and make it less likely for them to deviate from expected courses of action.
Originality/value
Combining different literature streams – street level bureaucracy, professionalism, network organisations and welfare governance – and building on an original case study, the paper contribute to understanding professionalism in welfare contexts increasingly characterised by the combination of bureaucratic, professional and network logics.
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Radha Subramanyam, Y. Adline Jancy and P. Nagabushanam
Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data…
Abstract
Purpose
Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.
Design/methodology/approach
Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.
Findings
Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.
Research limitations/implications
Other optimization techniques can be applied for WSN to analyze the performance.
Practical implications
Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.
Social implications
Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.
Originality/value
Literature survey is carried out to find the methods which give better performance.
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Ahmad Honarjoo and Ehsan Darvishan
This study aims to obtain methods to identify and find the place of damage, which is one of the topics that has always been discussed in structural engineering. The cost of…
Abstract
Purpose
This study aims to obtain methods to identify and find the place of damage, which is one of the topics that has always been discussed in structural engineering. The cost of repairing and rehabilitating massive bridges and buildings is very high, highlighting the need to monitor the structures continuously. One way to track the structure's health is to check the cracks in the concrete. Meanwhile, the current methods of concrete crack detection have complex and heavy calculations.
Design/methodology/approach
This paper presents a new lightweight architecture based on deep learning for crack classification in concrete structures. The proposed architecture was identified and classified in less time and with higher accuracy than other traditional and valid architectures in crack detection. This paper used a standard dataset to detect two-class and multi-class cracks.
Findings
Results show that two images were recognized with 99.53% accuracy based on the proposed method, and multi-class images were classified with 91% accuracy. The low execution time of the proposed architecture compared to other valid architectures in deep learning on the same hardware platform. The use of Adam's optimizer in this research had better performance than other optimizers.
Originality/value
This paper presents a framework based on a lightweight convolutional neural network for nondestructive monitoring of structural health to optimize the calculation costs and reduce execution time in processing.
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Yanghong Li, Yahao Wang, Yutao Chen, X.W. Rong, Yuliang Zhao, Shaolei Wu and Erbao Dong
The current difficulties of distribution network working robots are mainly in the performance and operation mode. On the one hand, high-altitude power operation tasks require high…
Abstract
Purpose
The current difficulties of distribution network working robots are mainly in the performance and operation mode. On the one hand, high-altitude power operation tasks require high load-carrying capacity and dexterity of the robot; on the other hand, the fully autonomous mode is uncontrollable and the teleoperation mode has a high failure rate. Therefore, this study aims to design a distribution network operation robot named Sky-Worker to solve the above two problems.
Design/methodology/approach
The heterogeneous arms of Sky-Worker are driven by hydraulics and electric motors to solve the contradiction between high load-carrying capacity and high flexibility. A human–robot collaborative shared control architecture is built to realize real-time human intervention during autonomous operation, and control weights are dynamically assigned based on energy optimization.
Findings
Simulations and tests show that Sky-Worker has good dexterity while having a high load capacity. Based on Sky-Worker, multiuser tests and practical application experiments show that the designed shared-control mode effectively improves the success rate and efficiency of operations compared with other current operation modes.
Practical implications
The designed heterogeneous dual-arm distribution robot aims to better serve distribution line operation tasks.
Originality/value
For the first time, the integration of hydraulic and motor drives into a distribution network operation robot has achieved better overall performance. A human–robot cooperative shared control framework is proposed for remote live-line working robots, which provides better operation results than other current operation modes.
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Qiang Wen, Lele Chen, Jingwen Jin, Jianhao Huang and HeLin Wan
Fixed mode noise and random mode noise always exist in the image sensor, which affects the imaging quality of the image sensor. The charge diffusion and color mixing between…
Abstract
Purpose
Fixed mode noise and random mode noise always exist in the image sensor, which affects the imaging quality of the image sensor. The charge diffusion and color mixing between pixels in the photoelectric conversion process belong to fixed mode noise. This study aims to improve the image sensor imaging quality by processing the fixed mode noise.
Design/methodology/approach
Through an iterative training of an ergoable long- and short-term memory recurrent neural network model, the authors obtain a neural network model able to compensate for image noise crosstalk. To overcome the lack of differences in the same color pixels on each template of the image sensor under flat-field light, the data before and after compensation were used as a new data set to further train the neural network iteratively.
Findings
The comparison of the images compensated by the two sets of neural network models shows that the gray value distribution is more concentrated and uniform. The middle and high frequency components in the spatial spectrum are all increased, indicating that the compensated image edges change faster and are more detailed (Hinton and Salakhutdinov, 2006; LeCun et al., 1998; Mohanty et al., 2016; Zang et al., 2023).
Originality/value
In this paper, the authors use the iterative learning color image pixel crosstalk compensation method to effectively alleviate the incomplete color mixing problem caused by the insufficient filter rate and the electric crosstalk problem caused by the lateral diffusion of the optical charge caused by the adjacent pixel potential trap.
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Ramin Rostamkhani and Thurasamy Ramayah
This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of…
Abstract
This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.
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Gianluca Elia, Gianpaolo Ghiani, Emanuele Manni and Alessandro Margherita
This study aims to present a methodology and a system to support the technical and managerial issues involved in anomaly detection within the reverse logistics process of an…
Abstract
Purpose
This study aims to present a methodology and a system to support the technical and managerial issues involved in anomaly detection within the reverse logistics process of an e-commerce company.
Design/methodology/approach
A case study approach is used to document the company’s experience, with interviews of key stakeholders and integration of obtained evidence with secondary data.
Findings
The paper presents an algorithm and a system to support a more efficient and smart management of reverse logistics based on a set of anticipatory actions, and continuous and automatic monitoring of returned goods. Improvements are described in terms of a number of key performance indicators.
Research limitations/implications
The analysis and the developed system need further applications and validations in other organizational contexts. However, the research presents a roadmap and a research agenda for the reverse logistics transformation in Industry 4.0, by also providing new insights to design a multidimensional performance dashboard for reverse logistics.
Practical implications
The paper describes a replicable experience and provides checklists for implementing similar initiatives in the domain of reverse logistics, in the aim to increase the company’s performance along four key complementary dimensions, i.e. time savings, accuracy, completeness of data analysis and interpretation and cost efficiency.
Originality/value
The main novelty of the study stays in carrying out a classification of anomalies by type and product category, with related causes, and in proposing operational recommendations, including process monitoring and control indicators that can be included to design a reverse logistics performance dashboard.
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Ali Beiki Ashkezari, Mahsa Zokaee, Erfan Rabbani, Masoud Rabbani and Amir Aghsami
Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This…
Abstract
Purpose
Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.
Design/methodology/approach
In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.
Findings
Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.
Originality/value
The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.
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Imoh Antai and Roland Hellberg
The total defence (TD) concept constitutes a joint endeavour between the military forces and civil defence structures within a TD state. Logistics is essential for such joint…
Abstract
Purpose
The total defence (TD) concept constitutes a joint endeavour between the military forces and civil defence structures within a TD state. Logistics is essential for such joint collaboration to work; however, the mismatch between military and civil defence logistics structures poses challenges for such joint collaboration. The purpose of this paper is to identify logistics concept areas within the TD framework that allow for military and civil defence collaborations from a logistics operations perspective.
Design/methodology/approach
Pattern-matching analysis is used to compare patterns found in the investigated case with those prescribed from the literature and predicted to occur. The study seeks to identify logistics concepts within TD from the literature and from the events describing the Swedish response to the Covid-19 pandemic. Pattern matching thus allows for the reconciliation of logistics concepts from the literature to descriptions of how the response was handled, albeit under a TD framework.
Findings
Findings show quite distinct foci between the theoretical and observational realms in terms of logistics applications. While the theoretical realm identifies four main logistics concepts, the observational realm identifies five logistics conceptual themes. This goes on to show an incongruence between the military and civil parts of the TD.
Research limitations/implications
This study provides basis for further research into the applications and management of logistics activity within TD and emergency response.
Originality/value
Logistics applications within TD have not, until now, received much attention in the literature. Given this knowledge gap, this study is of original value.
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