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.

Despite the rare use of the term ‘strategy’ in public and voluntary sector organizations, recent research has seen the use of both the strategy and strategy-as-practice concepts in regulating the innovation perspective within the public sector. The available literature on innovation, strategy, and service delivery within the public sector offers positive insights into forming a new concept of innovation within the public organization sphere. Using a systematic review, we aim to understand the integration of the strategy-as-practice perspective into the public service ethos to drive the innovation perspective forward. The review was performed in two stages, 855 documents were retrieved in the first stage that covered a five-year time span, while 8,620,000 documents were retrieved in the second stage that covered a twenty-three-year time span. We further supported our argument through a quantitative questionnaire with 93 respondents from Kuwait. The findings of the research indicate that public sector policymakers need to pay attention to the social complexity of their context in order to innovate delivered public services. Furthermore, policymakers need to adopt new innovative schemes including innovative strategy practices, digital governance, reform ethos, and mutual constitution in their strategies in order to ensure the innovative public services that are required by their communities.