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The performance of Wireless Sensor Networks (WSNs) applications is bounded by the limited resources of battery-enabled Sensor Nodes (SNs), which include energy and computational power; the combination of which existing research seldom focuses on. Although bio-inspired algorithms provide a way to control energy usage by finding optimal routing paths, those which converge slower require even more computational power, which altogether degrades the overall lifetime of SNs.

Hence, two novel routing protocols are proposed using the Red-Deer Algorithm (RDA) in a WSN scenario, namely Horizontal PEG-RDA Equal Clustering and Horizontal PEG-RDA Unequal Clustering, to address the limited computational power of SNs. Clustering, data aggregation and multi-hop transmission are also integrated to improve energy usage. Unequal clustering is applied in the second protocol to mitigate the hotspot problem in Horizontal PEG-RDA Equal Clustering.

Comparisons with the well-founded Ant Colony Optimisation (ACO) algorithm reveal that RDA converges faster by 85 and 80% on average when the network size and node density are varied, respectively. Furthermore, 33% fewer packets are lost using the unequal clustering approach which also makes the network resilient to node failures. Improvements in terms of residual energy and overall network lifetime are also observed.

Proposal of a bio-inspired algorithm, namely the RDA to find optimal routing paths in WSN and to enhance convergence rate and execution time against the well-established ACO algorithm. Creation of a novel chain cluster-based routing protocol using RDA, named Horizontal PEG-RDA Equal Clustering. Design of an unequal clustering equivalent of the proposed Horizontal PEG-RDA Equal Clustering protocol to tackle the hotspot problem, which enhances residual energy and overall network lifetime, as well as minimises packet loss.

With the increasing acclaim of Wireless Sensor Networks and its diverse applications, research has been directed into optimising and prolonging the network lifetime. Energy efficiency has been a critical factor due to the energy resource impediment of batteries in sensor nodes. The proposed routing algorithm therefore aims at extending lifetime of sensors by enhancing load distribution in the network. The scheme is based on the chain-based routing technique of the PEGASIS (Power Energy GAthering in Sensor Information Systems) protocol and uses Ant Colony Optimisation to obtain the optimal chain. The contribution of the proposed work is the integration of the clustering method to PEGASIS with Ant Colony Optimisation to reduce redundancy of data, neighbour nodes distance and transmission delay associated with long links, and the employment an appropriate cluster head selection method. Simulation results indicates proposed method’s superiority in terms of residual energy along with considerable improvement regarding network lifetime, and significant reduction in delay when compared with existing PEGASIS protocol and optimised PEG-ACO chain respectively.

Due to its boundless potential applications, Wireless Sensor Networks have been subject to much research in the last two decades. WSNs are often deployed in remote environments making replacement of batteries not feasible. Low energy consumption being of prime requisite led to the development of energy-efficient routing protocols. The proposed routing algorithms seek to prolong the lifetime of sensor nodes in the relatively unexplored area of 3D WSNs. The schemes use chain-based routing technique PEGASIS as basis and employ genetic algorithm to build the chain instead of the greedy algorithm. Proposed schemes will incorporate an energy and distance aware CH selection technique to improve load balancing. Clustering of the network is also implemented to reduce number of nodes in a chain and hence reduce delay. Simulation of our proposed protocols is carried out for homogeneous networks considering separately cases for a static base-station inside and outside the network. Results indicate considerable improvement in lifetime over PEGASIS of 817% and 420% for base station inside and outside the network respectively. Residual energy and delay performance are also considered.

This research aims to provide a conceptual framework with the scope to assist in establishing sustainable supply chain clusters (SCCs) by providing an instrument for organisations to enhance the three sustainability dimensions in a dynamic environment.

This research proposes a conceptual framework to enhance sustainability and organisational performance through three theoretical lenses: the system theory, extended resource-based view and the dynamic capabilities (DCs) theory. This approach is carried out through a comprehensive review of the existing literature on SCCs.

Four main propositions are formulated and demonstrated using the developed framework, which expands the discussion about SCCs and their key characteristics in a dynamic environment. This is particularly relevant as it allows empirical testing of the theories in an SCC context.

It can be noted that more extensive research is needed to further understand the issues faced in establishing sustainable clusters. Drawing on the theoretical lenses to establish the framework helps to enhance the understanding and operational capabilities of sustainable SCCs during and after disruptions, such as the global disruption created by COVID-19.

This research paves the way to help organisations improve their adaptability to the dynamic business environment by emphasizing the importance of clustering and linking it to sustainability through DCs to establish a sustainable cluster.

This research aims to guide organisations' use of SCCs as tools to enhance sustainability in a dynamic environment, given that the relationship amongst supply chain cluster design characteristics (SCCDCs), DCs and sustainability remains unexplored. The combination of the three theoretical lenses in developing the proposed framework will assist in further understanding the applicability of these theories when they are considered together.

Load balancing is an effective enhancement to the proposed routing protocol, and the basic idea is to share traffic load among cluster members to reduce the dropping probability due to queue overflow at some nodes. This paper aims to propose a novel hierarchical approach called distributed energy efficient adaptive clustering protocol (DEACP) with data gathering, load-balancing and self-adaptation for wireless sensor network (WSN). The authors have proposed DEACP approach to reach the following objectives: reduce the overall network energy consumption, balance the energy consumption among the sensors and extend the lifetime of the network, the clustering must be completely distributed, the clustering should be efficient in complexity of message and time, the cluster-heads should be well-distributed across the network, the load balancing should be done well and the clustered WSN should be fully connected. Simulations show that DEACP clusters have good performance characteristics.

A WSN consists of large number of wireless capable sensor devices working collaboratively to achieve a common objective. One or more sinks [or base stations (BS)] which collect data from all sensor devices. These sinks are the interface through which the WSN interacts with the outside world. Challenges in WSN arise in implementation of several services, and there are so many controllable and uncontrollable parameters (Chirihane, 2015) by which the implementation of WSN is affected, e.g. energy conservation. Clustering is an efficient way to reduce energy consumption and extend the life time of the network, by performing data aggregation and fusion to reduce the number of transmitted messages to the BS (Chirihane, 2015). Nodes of the network are organized into the clusters to process and forwarding the information, while lower energy nodes can be used to sense the target, and DEACP makes no assumptions on the size and the density of the network. The number of levels depends on the cluster range and the minimum energy path to the head. The proposed protocol reduces the number of dead nodes and the energy consumption, to extend the network lifetime. The rest of the paper is organized as follows: An overview of related work is given in Section 2. In Section 3, the authors propose an energy efficient level-based clustering routing protocol (DEACP). Simulations and results of experiments are discussed in Section 4. In Section 5, the authors conclude the work presented in this paper and the scope of further extension of this work.

The authors have proposed the DEACP approach to reach the following objectives: reduce the overall network energy consumption, balance the energy consumption among the sensors and extend the lifetime of the network, the clustering must be completely distributed, the clustering should be efficient in complexity of message and time, the cluster-heads should be well-distributed across the network, the load balancing should be done well, the clustered WSN should be fully connected. Simulations show that DEACP clusters have good performance characteristics.

The integration of e‐business and supply chain enables seamless information flow from suppliers to customer service network via the internet. It also enables better‐coordinated materials flow from customer order to production, storage, distribution and delivery. The purpose of this paper is to describe the work that leads to the realisation of a hierarchical model for e‐supply chain coordination and optimisation.

The model is based on an e‐business information flow network in order to respond rapidly to the dynamics of e‐supply chain and market. It can be used to realize management level strategies, and facilitate the planning and control of detailed operation schedules of supply chain units in an e‐supply chain environment. Three main modules are discussed. They are routing and sequence optimiser (RSO) with the aid of a GA and TS‐based multiple population search strategy (MPSS); supply chain virtual clustering (SCVC) based on fuzzy virtual clustering; and supply chain order scheduling (SCOS) using an agent‐based distributed scheduling system.

These modules enable: the generation of preferred routings, transportation modes and work order plan under such constraints as customer service level, cycle time and cost; the formation of supply chain's unit‐transportation‐work order families using a clustering approach to down‐size supply chain problems and increase computation efficiency; and the integration of scheduling with supply chain optimisation in order to facilitate the control of a supply chain with the aid of an agent‐based distributed scheduling approach.

This paper proposed a hierarchical model for e‐supply chain coordination and optimisation that is capable to solve large‐scale problems. A MPSS using GA and TS was depicted in detail to expedite the RSO.

In particular, this paper aims to systematically analyze a few prominent wireless sensor network (WSN) clustering routing protocols and compare these different approaches according to the taxonomy and several significant metrics.

In this paper, the authors have summarized recent research results on data routing in sensor networks and classified the approaches into four main categories, namely, data-centric, hierarchical, location-based and quality of service (QoS)-aware, and the authors have discussed the effect of node placement strategies on the operation and performance of WSNs.

Performance-controlled planned networks, where placement and routing must be intertwined and everything from delays to throughput to energy requirements is well-defined and relevant, is an interesting subject of current and future research. Real-time, deadline guarantees and their relationship with routing, mac-layer, duty-cycles and other protocol stack issues are interesting issues that would benefit from further research.

This paper aims to investigate the effect of institutional logics on the intended resource coordination and integration in extended enterprises (EEs).

The qualitative multiple case study approach collected data from three EEs and their hierarchical organizational context in the restructured and privatized railway sector of the Netherlands by observing 40 meetings, conducting 31 semi-structured interviews and 9 feedback meetings and perusing organizational documents.

Performance and professional logics characterized the EEs and their hierarchical organizational context. Aligning these logics failed to support the resource coordination and integration in the EEs because of the logics’ resource-centric nature. The co-creation logic in one of the EEs mitigated this resource centrism by addressing the resource personifications and representations of the professional and performance logics. Business unit representatives having hierarchically overlapping organizational positions supported this change process by offering protection from resource-centric logics.

The chosen research design limits the generalization of the findings but reveals new scientific and practical insights on the role of institutional logics for sustaining EEs.

The various EE business-units, but especially their contract and concession authorities, need to realize the crippling effect of resource-centric logics on sustaining an EE. Becoming aware of the resource personifications and representations of these logics can assist in addressing their negative effects.

No previous studies have empirically investigated the effect of institutional logics on the intended resource coordination and integration in EEs.

The purpose of this study is to describe the determinants of profitability in terms of the strategic profitability model (the Du Pont model), depicting the “route” to high profitability in grocery retail stores located in market areas possessing dissimilar competitive conditions.

Different physical characteristics (e.g. store formats) have traditionally been used as control criteria, but it is argued in this paper that management principles in retail chains should be based on different clusters of stores, formed from local competitive conditions. The paper proposes a clustering method based on five indicators of local competition. The research results are derived from local competitive conditions and the performance of 168 supermarkets, located in Sweden, and controlled by one retail chain.

The paper identifies four clusters of local markets labeled monopoly, fleet market, venue, and duopoly, based on local competitive conditions. The findings show that the “route” to profitability significantly differs between the clusters. In monopoly the route to high profitability goes through high‐gross margin, while in fleet market the key figures are low cost, large number of shoppers per week, and high productivity. Venue and duopoly both gain from high‐average transactions per shopper.

Supermarkets under different competitive conditions have different critical success factors and would probably be better managed, supported and evaluated on a different basis, i.e. retail chains need to adjust their approach to their supermarkets depending on local competitive conditions.

Based on the findings the paper proposes unique management strategies for different clusters of local markets to further enhance current strength areas.

The COVID-19 pandemic has brought unprecedented disruptions to global supply chains, compelling organizations to reevaluate their strategies for resilience and adaptability. In response, smart technologies (ST) have emerged as integral tools in post-pandemic supply chain management (SCM). This study aims to conduct an exploratory systematic literature review to comprehensively examine the evolving landscape of smart technology adoption in the context of SCM post-pandemic.

A systematic literature review has been conducted to examine the potential research contribution or directions in the field of ST and SCM. In total, 240 articles were shortlisted from the SCOPUS database in the chosen field of research. Bibliometric analysis was conducted by using VOSviewer to investigate the research trends in the area of SCM.

The review identifies key themes and trends, including supply chain resilience, digital transformation, enhanced visibility, predictive analytics and sustainability considerations. It explores the role of ST in fostering agility, transparency and risk mitigation within supply chains. Furthermore, eight clusters were identified to generate several thematic topics of ST in SCM. The results have evidenced a strong gap related to Industry 5.0 approaches for the supply chain field. A total of 240 publications, including journal articles, have been found in the literature. A total of 37 words, which were grouped in 8 clusters, have been identified in the data analysis.

By synthesizing the current state of literature, this study provides valuable insights for practitioners, policymakers and researchers seeking to navigate the complexities of post-pandemic SCM in an increasingly digitized and interconnected world. The findings highlight the transformative potential of ST and offer a roadmap for further exploration in this critical domain.

In this paper, the development path of the field of ST in SCM during the pandemic and the research constructs are presented and potential research directions are based on the bibliometric method.