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The purpose of this paper is to present a new particle swarm optimization (PSO) algorithm called HelixPSO for finding ribonucleic acid (RNA) secondary structures that have a low energy and are similar to the native structure.

Two variants of HelixPSO are described and compared to the recent algorithms Rna‐Predict, SARNA‐Predict, SetPSO and RNAfold. Furthermore, a parallel version of the HelixPSO is proposed.

For a set of standard RNA test sequences it is shown experimentally that HelixPSO obtains a better average sensitivity than SARNA‐Predict and SetPSO and is as good as RNA‐Predict and RNAfold. When best values for different measures (e.g. number of correctly predicted base pairs, false positives and sensitivity) over several runs are compared, HelixPSO performs better than RNAfold, similar to RNA‐Predict, and is outperformed by SARNA‐Predict. It is shown that HelixPSO complements RNA‐Predict and SARNA‐Predict well since the algorithms show often very different behavior on the same sequence. For the parallel version of HelixPSO it is shown that good speedup values can be obtained for small to medium size PC clusters.

The new PSO algorithm HelixPSO for finding RNA secondary structures uses different algorithmic ideas than the other existing PSO algorithm SetPSO. HelixPSO uses thermodynamic information as well as the centroid as a reference structure and is based on a multiple swarm approach.

The purpose of this paper is to understand conflicts that emerge between managers of buying and supplying firms when a personal relationship (friendship, etc.) is present between them in the supply chain context.

This research uses a case study methodology and relies on data obtained from 30 qualitative interviews with managers of buying and supplying firms, having a personal relationship within inter-firm relationships to promote the interest of the firm.

Results from this study reveal conflicts between managers of buying and supplying firms due to the presence of a personal relationship between them. Specifically, results suggest that managers face ego conflict, supplier’s selection conflict and conflict on accepting late deliveries when they rely on personal relationships, which are themselves embedded within inter-firm relationship.

This study has some limitations. First, this study examines behavioural patterns in Australian cultural context. Second, results of this study are not generalizable to a broader population.

Firms can use the findings to understand conflicts, which arise between managers of buying and supplying firms, as a result of a personal relationship between them in the supply chain.

This is, perhaps, the first study contributing to the supply chain relationship literature by unveiling conflicts between managers of buying and supplying firms, when a personal relationship is present between them.

The aim of this paper is to explore the potential of particle swarm optimization (PSO) algorithm to solve an electromagnetic inverse problem.

A modified PSO algorithm is designed.

The modified PSO algorithm is a more stable, robust and efficient global optimizer for solving the well-known benchmark optimization problems. The new mutation approach preserves the diversity of the population, whereas the proposed dynamic and adaptive parameters maintain a good balance between the exploration and exploitation searches. The numerically experimental results of two case studies demonstrate the merits of the proposed algorithm.

Some improvements, such as the design of a new global mutation mechanism and introducing a novel strategy for learning and control parameters, are proposed.

The purpose of this paper is to propose an optimal energy management (OEM) method using intelligent optimization techniques applied to implement an optimally hybrid heat and power isolated microgrid. The microgrid investigated combines renewable and conventional power generation.

Five bio-inspired optimization methods include an advanced proposed multi-objective particle swarm optimization (MOPSO) approach which is comparatively applied for OEM of the implemented microgrid with other bio-inspired optimization approaches via their comparative simulation results.

Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization methods. Moreover, the proposed MOPSO is successfully applied to perform 24-h OEM microgrid. The simulation results also display the merits of the real time optimization along with the arbitrary of users’ selection as to satisfy their power requirement.

This paper focuses on the OEM of a designed microgrid using a newly proposed modified MOPSO algorithm. Optimal multi-objective solutions through Pareto front demonstrate that the advanced proposed MOPSO method performs quite better in comparison with other meta-heuristic optimization approaches.

The purpose of this paper is to explore the role of interpersonal relationships (IPRs) in service supply chain integration (SSCI) in terms of strategic alliance, information integration, and process integration.

The research employs an exploratory/investigational approach to multiple case studies and empirically investigates effects of IPRs in SSCI. The data were mainly collected through semi-structured interviews with senior management staff from four service companies and their suppliers or customers in New Zealand. Archival data from the Internet and company documentations were also applied.

The authors find that three dimensions of IPRs influence SSCI in different ways. The effect of IPRs on SSCI is indirect: personal affection acts as an initiator, and personal credibility works as a “gate-keeper” and strengthens the confidence of interactive partners, while personal communication, a facilitator, plays a more important role in SSCI than personal affection and credibility.

The research provides managers in service supply chains the awareness of the importance of IPRs, as well as the characteristics of IPRs, in order to best utilize available resources. Managers should synergize all three dimensions of IPRs’ resources: make efforts to cultivate personal affection to avoid the instinctive isolation modern technology brings; attempt to accumulate positive personal credibility profiles; focus more on the role of personal communication and retain physical contact in SSCI processes.

This study contributes to SSCI literature by extending from the inter-organizational relationships (IORs) to interpersonal level relationships to explore the inner influence mechanism. Also, it explores the role of IPRs on all three dimensions of SSCI simultaneously rather than individual dimensions independently. Finally, it contributes to resource orchestration theory (ROT) by synthesizing three dimensions of IPRs resources, and IORs resources in order to achieve capabilities of SSCI. The study develops the individual-level research in supply chain integration (SCI) to a further depth.

In this paper, we present a new hybrid binary version of bat and enhanced particle swarm optimization algorithm in order to solve feature selection problems. The proposed algorithm is called Hybrid Binary Bat Enhanced Particle Swarm Optimization Algorithm (HBBEPSO). In the proposed HBBEPSO algorithm, we combine the bat algorithm with its capacity for echolocation helping explore the feature space and enhanced version of the particle swarm optimization with its ability to converge to the best global solution in the search space. In order to investigate the general performance of the proposed HBBEPSO algorithm, the proposed algorithm is compared with the original optimizers and other optimizers that have been used for feature selection in the past. A set of assessment indicators are used to evaluate and compare the different optimizers over 20 standard data sets obtained from the UCI repository. Results prove the ability of the proposed HBBEPSO algorithm to search the feature space for optimal feature combinations.

The promotion mix is the combination of personal selling, advertising, and sales promotion used to achieve marketing objectives. The objective‐and‐task method is used in practice to develop a single promotion mix plan. This is practical but has drawbacks: (1) only one promotion strategy and mix is considered, and (2) decision making is taken out of the hands of senior marketing management. This paper sets forth a decision‐making process by which alternative promotion strategies and mixes are generated so that senior marketing management can choose the one that is most promising.

The purpose of this paper is to present an approach for the decentralization of swarm intelligence algorithms that run on computing systems with autonomous components that are connected by a network. The approach is applied to a particle swarm optimization (PSO) algorithm with multiple sub‐swarms. PSO is a nature inspired metaheuristic where a swarm of particles searches for an optimum of a function. A multiple sub‐swarms PSO can be used for example in applications where more than one optimum has to be found.

In the studied scenario the particles of the PSO algorithm correspond to data packets that are sent through the network of the computing system. Each data packet contains among other information the position of the corresponding particle in the search space and its sub‐swarm number. In the proposed decentralized PSO algorithm the application specific tasks, i.e. the function evaluations, are done by the autonomous components of the system. The more general tasks, like the dynamic clustering of data packets, are done by the routers of the network.

Simulation experiments show that the decentralized PSO algorithm can successfully find a set of minimum values for the used test functions. It was also shown that the PSO algorithm works well for different type of networks, like scale‐free network and ring like networks.

The proposed decentralization approach is interesting for the design of optimization algorithms that can run on computing systems that use principles of self‐organization and have no central control.

Contemporary working life highlights the challenge between exploitation and exploration both on a general and a more individual level. Here, we focus on the latter, and connect the critical debate regarding self-management to March's exploitation/exploration trade-off, as this forms a useful theoretical frame to understand how employees make sense of their self-management efforts. The employee is subjected to an individual responsibility to understand and manage an exploration of the self while handling the norms of self-exploitation that a self-management culture creates. Through an empirical study of a large group of management consultants, we explore how they perform and make sense of self-exploitation and self-exploration through three specific discourses: the discourse of workload, the discourse of aspiration, and the discourse of fun. Through these, the consultants try to identify optimal amounts of work, play, and ambition, all while handling the trade-off between self-exploitation and self-exploration. We show how this keeps failing, but how it reappears as a necessary condition for avoiding future failures. In all three discourses, the trade-off therefore presents itself as the problem of as well as the solution to self-management.

The objective of this paper is to document and analyze the organizational activities of faculty members using a personal information management (PIM) framework developed by Jacques (2016).

Interviews were carried out with seven faculty members, focusing on their personal information organization practices as they relate to their academic activities. These interviews took the form of a guided tour of informants' digital workspaces.

Analyses focused on PIM activities make it possible to identify the different strategies adopted by faculty members to organize their academic personal information. This qualitative approach highlights four activities involved in the organization of personal information: inclusion, exclusion, apprehension and implementation. It also reveals differences in the ability of faculty members to analyze their own practices. Finally, the relationship to time and memory of PIM practices is examined through the lens of the concepts of virtualization and actualization.

This research provides a more nuanced understanding of PIM practices, specifically of organizational activities, by considering the meaning of these practices for individuals as part of their daily lives. It aims to foster literacy by facilitating the interactions of individuals with their personal information through educational activities.