This paper addresses the problem of activity scheduling and operator assignment in workstations of aerospace assembly lines. The problem is modelled as a new variant of the Multi-Mode Resource Constrained Project Scheduling Problem (MRCPSP), which incorporates practical features from aerospace workstations in assembly lines. These workstations have a substantial number of activities to be scheduled within a given assembly cycle time. It introduces particularities which are not usually addressed such as considering additional workers for performing activities, different workers’ proficiency, and spatial limitations in work zones. The objective is to schedule the activities of an aerospace workstation, minimising the total labour cost, while satisfying the cycle time and the zone’s limitations. The problem is initially formulated by employing mixed-integer linear programming methods with mathematical modelling and solved using two different algorithms: an Ant Colony System (ACS) and a memetic ACS. Given the novelty of the problem presented, new sets of benchmark cases of different sizes for this problem are also proposed and solved. To assess the performance of the algorithms, the solutions for the small-sized instances are compared in terms of deviation with the results obtained by an optimisation modelling software. Further experimentation with the algorithms is carried out with medium and large instances, showing good performance and providing reasonably good results in realistic problems.

The Diels-Alder cycloaddition of cyclopentadienone derivative 3-methyl-5,6,7,8-tetrahydroazulen-1(4H)-one with a series of maleimide derivatives is studied using Molecular Electron Density Theory at the B3LYP/6-311++G(d,p) computational level. Conceptual Density Functional Theory analysis predicts low reaction polarity, which is confirmed by global electron density transfer analysis at the transition structures. Topological analysis reveals the electron distribution and evolution of multiple covalent and non-covalent interactions at the transition structures. The results indicate that these Diels-Alder reactions follow an asynchronous one-step mechanism under kinetic control, favouring the endo product formation. Bonding Evolution Theory shows that the reaction mechanism can further be decomposed into five distinct bonding evolution phases. In addition, a molecular docking study is conducted to assess the antimicrobial potential of the reaction products against Escherichia coli and Staphylococcus aureus. An evaluation of the results of binding affinity and molecular interactions concludes that the products are viable as antimicrobial agents.

Production scheduling is a crucial task in the manufacturing process. In this way, the managers must decide the job's production schedule. However, this task is not simple, often requiring complex software tools and specialized algorithms to find the optimal solution. In this work, a multi-objective optimization model was developed to explore production scheduling performance measures to help managers in decision-making related to job attribution under three simulations of parallel machine scenarios. Five important production scheduling performance measures were considered (makespan, tardiness and earliness times, number of tardy and early jobs), and combined into three objective functions. To solve the scheduling problem, three multi-objective evolutionary algorithms are considered (Multi-objective Particle Swarm Optimization, Multi-objective Grey Wolf Algorithm, and Non-dominated Sorting Genetic Algorithm II), and the set of optimum solutions named Pareto Front, provided by each one is compared in terms of dominance, generating a new Pareto Front, denoted as Final Pareto Front. Furthermore, this Final Pareto Front is analyzed through an automatic bio-inspired clustering algorithm based on the Genetic Algorithm. The results demonstrated that the proposed approach efficiently solves the scheduling problem considered. In addition, the proposed methodology provided more robust solutions by combining different bio-inspired multi-objective techniques. Furthermore, the cluster analysis proved fundamental for a better understanding of the results and support for choosing the final optimum solution.

Modern Smart Cities are highly dependent on an efficient energy service since electricity is used in an increasing number of urban activities. In this regard, Time-of-Use prices for electricity is a widely implemented policy that has been successful to balance electricity consumption along the day and, thus, diminish the stress and risk of shortcuts of electric grids in peak hours. Indeed, residential customers may now schedule the use of deferrable electrical appliances in their smart homes in off-peak hours to reduce the electricity bill. In this context, this work aims to develop an automatic planning tool that accounts for minimizing the electricity costs and enhancing user satisfaction, allowing them to make more efficient usage of the energy consumed. The household energy consumption planning problem is addressed with a multiobjective evolutionary algorithm, for which problem-specific operators are devised, and a set of state-of-the-art greedy algorithms aim to optimize different criteria. The proposed resolution algorithms are tested over a set of realistic instances built using real-world energy consumption data, Time-of-Use prices from an electricity company, and user preferences estimated from historical information and sensor data. The results show that the evolutionary algorithm is able to improve upon the greedy algorithms both in terms of the electricity costs and user satisfaction and largely outperforms to a large extent the current strategy without planning implemented by users.

This study conducts a comprehensive bibliometric analysis to explore the nexus of technology applications and innovation performance within the realm of supply chain management (SCM). Despite the increasing importance of smart supply chain management in modern organizations, there is a paucity of research dedicated to this intersection. The primary objective is to identify trends, research gaps, and emerging themes in the literature concerning SSCM, technology applications, and innovation performance. Leveraging the Web of Science database, bibliometric analysis is employed to analyze existing literature, revealing insights into strategies for harnessing technology-driven innovations in SCM. By embracing sustainability principles, companies can position themselves as leaders in an increasingly interconnected and environmentally conscious world, generating long-term value for both them and society.

This paper deals with the problem of scheduling jobs in a parallel flow shop environment without buffers between machines and with sequence-dependent setup times in order to minimize the maximum completion time of jobs. The blocking constraint normally leads to an increase in the maximum completion time of jobs due to the blockage of machines, which can increase even more so when setup times are considerable. Hence, the heuristic to solve this problem must take into account these specificities in order to minimize the timeout of machines. Because the procedures designed to solve the parallel flow shop scheduling problem must deal not only with the sequencing of jobs but also with their allocation to the flow shops, 36 heuristics have been tested in this paper, of which 35 combine sequencing rules with allocation methods while the last one takes a different approach that is more related to the nature of this problem. The computational evaluation of the implemented heuristics showed good performance of the heuristic designed especially for the problem (RCP0) when the setup times are considerable. Furthermore, the evaluation has also allowed us to propose a combined heuristic that leads to good solutions in a short CPU time.

The examination of accounting practices within the corporate supply chain is recognized as a crucial workplace concern, employing a bibliometric survey approach. This study seeks to elucidate the correlation between legal compliance and financial integrity within accounting practices in the corporate supply chain. The findings are derived from a bibliometric analysis. Furthermore, the analysis reveals an increasing trend in publications related to the study's keywords over the past decade. Theoretical and practical implications are explored and discussed.

This paper aims to use a dual-process of direct and indirect use of competitive advantage (CA) for investigation of the contribution of customer orientation (CO) in affecting organizational performance (OP) of Jordanian banks. The current empirical research is based on the survey conducted on 16 banks from Jordan. Structural equation modeling was employed along with confirmatory factor analysis for easy comprehension of correlation among the three latent constructs. The results showed that (OP) experienced a partial reconciliation effect of (CO) in the presence of (CA). The study also established the significant immediate impact on performance of organization because of (CO). Moreover, significant indirect positive effect of (CO) over (OP) was evident in presence of (CA). Theoretical and managerial inferences of the outcomes are explained in the last section.

The purpose of this study is to analyse the effects of (1) quintuple helix on small and medium enterprises (SMEs) performance; (2) ability of SMEs on SMEs performance; (3) quintuple helix on ability of SMEs; (4) innovation on SMEs performance and (5) innovation on ability of SMEs. The analysis uses quantitative analysis, as a descriptive analysis as well as inferential statistics. Respondents are taken from the population of the craft subsector of creative industries, governments, academicians, media-based and culture-based public, in addition to natural environments of society in creative industrial cluster cities in Spain (50 samples) and Indonesia (50 samples). The results of the study identify the significant influence of: (1) quintuple helix on SMEs performance; (2) ability on SMEs performance; and (5) innovation on ability of SMEs. On the other hand, they show the non-significant influence of (3) quintuple helix on ability of SMEs and (4) innovation on SMEs performance in craft cluster creative industry in Indonesia. Regarding the craft creative industry in Spain, the results show the significant influence of (2) ability of SMEs on SMEs performance, (3) quintuple helix on ability of SMEs; (4) innovation on SMEs performance and (5) innovation on ability of SMEs, but the non-significant influence of (1) quintuple helix on SMEs performance. The comparative study results show that the relationship of (2) ability of SMEs on SMEs performance, (5) innovation on ability of SMEs, both in Indonesia and Spain, were significant. On the other hand, there are some significant relationship of (3) quintuple helix on ability of SMEs and (4) innovation on SMEs performance in Spain but such relationships do not exist in Indonesia. Moreover, while the effect of (1) quintuple helix on SMEs performance is significant in Indonesia, it is not significant in Spain. Furthermore, the mediation function shows the inverted result on indirect relationship of quintuple helix on SMEs performance through ability of SMEs in Indonesia, but full mediation in Spain, whereas the effect of innovation on SMEs performance through ability of SMEs is observed as full mediation in Indonesia, but partial mediation in Spain.

This study investigates the impact of risk management and agile methodology on the success of cybersecurity projects, emphasizing the mediating role of team collaboration within the financial sector. Based on a sample of 229 professionals, including IT specialists, project managers, and risk officers, data was collected using a structured survey instrument and analyzed through Structural Equation Modeling (SEM) using SmartPLS. The results confirm that both risk management and agile methodology have direct positive effects on cybersecurity project success. Additionally, both factors significantly enhance team collaboration, which in turn positively influences project outcomes, thereby confirming its mediating role in the relationship between these variables and cybersecurity project success. All proposed hypotheses were supported. The findings highlight the crucial interplay between management practices and team dynamics in ensuring project success. The findings also provide valuable theoretical insights and practical implications for enhancing cybersecurity initiatives in the financial industry.