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1 – 2 of 2Mohammad Yaghtin and Youness Javid
The purpose of this research is to address the complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup…
Abstract
Purpose
The purpose of this research is to address the complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance. The primary goal is to minimize total tardiness, earliness and total completion times simultaneously. This study aims to provide effective solution methods, including a Mixed-Integer Programming (MIP) model, an Epsilon-constraint method and the Nondominated Sorting Genetic Algorithm (NSGA-II), to offer valuable insights into solving large-sized instances of this challenging problem.
Design/methodology/approach
This study addresses a multiobjective unrelated parallel machine scheduling problem with sequence-dependent setup times and periodic machine maintenance activities. An MIP model is introduced to formulate the problem, and an Epsilon-constraint method is applied for a solution. To handle the NP-hard nature of the problem for larger instances, an NSGA-II is developed. The research involves the creation of 45 problem instances for computational experiments, which evaluate the performance of the algorithms in terms of proposed measures.
Findings
The research findings demonstrate the effectiveness of the proposed solution approaches for the multiobjective unrelated parallel machine scheduling problem. Computational experiments on 45 generated problem instances reveal that the NSGA-II algorithm outperforms the Epsilon-constraint method, particularly for larger instances. The algorithms successfully minimize total tardiness, earliness and total completion times, showcasing their practical applicability and efficiency in handling real-world scheduling scenarios.
Originality/value
This study contributes original value by addressing a complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance activities. The introduction of an MIP model, the application of the Epsilon-constraint method and the development of the NSGA-II algorithm offer innovative approaches to solving this NP-hard problem. The research provides valuable insights into efficient scheduling methods applicable in various industries, enhancing decision-making processes and operational efficiency.
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Keywords
This research aims to examine the challenges of recruiting participatory action research (PAR) in managing innovation projects. An enhanced methodology based on PAR was developed…
Abstract
Purpose
This research aims to examine the challenges of recruiting participatory action research (PAR) in managing innovation projects. An enhanced methodology based on PAR was developed to mitigate the challenges related to recruiting PAR in managing innovation projects. The proposed methodology was evaluated by comparing it to established methodologies/frameworks such as Scrum, Design Thinking (DT) and The Lean Startup (TLS). The evaluation aimed to determine the advantages and limitations of the proposed methodology in managing innovation projects.
Design/methodology/approach
The proposed enhanced methodology consists of eight steps, ranging from developing an understanding of the industry and business structure to learning and knowledge management. In addition, the enhanced methodology uses other techniques, such as Force field analysis and 12 boundary questions.
Findings
The research findings indicate that using the proposed methodology can improve the formalization of collaboration in PAR, enabling the organization to respond better to market changes. It helps define the project scope more clearly, encouraging innovation, addressing communication barriers and considering different worldviews and practical issues. Based on the findings, the proposed enhanced methodology could complement other methodologies/frameworks such as Scrum, DT and TLS.
Research limitations/implications
The current research adds to the existing literature by identifying the challenges of recruiting PAR in managing innovation projects. A deductive reasoning process was utilized because there is no comprehensive research concerning the challenges of recruiting PAR in managing innovation projects. On the other hand, the PAR 4-phase cycle has been reviewed and enhanced to manage innovation projects.
Practical implications
The proposed methodology was used in a new product development project. The case study was done on one of the payment service provider companies that design, develop and deploy a digital product for marketing, installation, repair and maintenance of electronic funds transfer at point of sale devices.
Originality/value
No research has yet sought to identify the challenges of using PAR in innovation project management (IPM). Identifying the challenges associated with applying PAR in the IPM and providing an enhanced methodology to mitigate the challenges could fill a gap in IPM studies.
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