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A two-stage real world serial batching scheduling problem: a case study
No full textThis paper concerns a real-life production management problem composed of two stages, which includes interdependent batch scheduling problems. Moreover, both stages require setup operations at the beginning and between the subsequent batches. From the optimisation point of view, this production management problem is complying with customers' deadlines and hence minimising total lateness. To achieve this objective, the production planner must identify optimum or near-optimum batch schedules for both stages. Correspondingly, this paper aims to develop a methodology to manage the related production problem as accurately as possible. We formulate an optimisation model that employs the mathematical programming method in line with this. Afterwards, an algorithmic proposal based on the simulated annealing algorithm is also developed to solve the problem in realistic sizes. The computational capabilities of the developed model and the algorithm are evaluated on the randomly generated problem sets. A direct comparison between the mathematical model and the algorithm shows how efficiently the proposed algorithm solves real-world problems. Also, computational results indicate that the proposed algorithm satisfactorily solves the related real-world batch scheduling problem.Management || Operations Research & Management Scienc
Mediated public diplomacy and peace journalism: International public news agencies on the Syrian crisis
No full textAs the liberal international order has been falling, the heteropolar order coupled with politics of uncertainty has been rising. In this context, illiberal regimes of status-seeking powers have realized the value of public diplomacy to promulgate their versions of the reality. Those illiberal regimes' adoption of public diplomacy tools (incl. international public news agencies) has generated discussions on theoretical and practical approaches to the field at the intersection of political science/international relations, media, and communication studies. Against this backdrop, this paper aims to contribute to the emerging literature on public diplomacy of non-Western illiberal democracies. With the assumption that those regimes' illiberal democratic characteristics will be reflected in their public agencies' coverage styles (e.g., monologic, conflictive, and unbalanced), the article raises the following question: How do illiberal democracies utilize international public agencies as public diplomacy channels? To answer this question, it compares framing strategies (peace/war journalism) of the Russian TASS and the Turkish Anatolian Agency public agencies during the Syrian crisis. The findings reveal that those illiberal regimes' public agencies have reported the crisis as a state-centric monolog in conflict with the West by distrupting the global public good (i.e., peace).Communicatio
A Demand for Narrative: Reading Sabahattin Ali's Novel Kuyucaklı Yusuf as a Quest for Identity
No full textSabahattin Ali's first novel, Kuyucakl & imath || Yusuf, published in 1937, is a historically significant text within Turkish literature || it is the first realistic novel about Anatolian life and is a critique of the social system. However, the novel remained incomplete due to Ali's murder in 1948 amid a rising tide of authoritarianism and nationalism that he consistently critiqued. This study examines the novel's demand for narrative identity in the context of its creator's untimely death. The study reveals three obstacles: the silent language of victimhood, the extreme experience of loneliness, and the finality of the author's death, all of which function as barriers to realizing personal narratives. This exploration is also an attempt at an act of sepulcher, as defined by Paul Ricoeur, which means mourning the author's death by revising the incompleteness of Yusuf's identity. Ali's novel is an example of an ethical mode of authoring that requires giving up authoritative control over real or fictional life stories. Acknowledging the existence of untold stories alongside the potential for new narratives attests to the power of storytelling through the vulnerability of a life story.Humanities, Multidisciplinar
Solving blocking flowshop scheduling problem with makespan criterion using q-learning-based iterated greedy algorithms
No full textThis study proposes Q -learning -based iterated greedy (IGQ) algorithms to solve the blocking flowshop scheduling problem with the makespan criterion. Q learning is a model -free machine intelligence technique, which is adapted into the traditional iterated greedy (IG) algorithm to determine its parameters, mainly, the destruction size and temperature scale factor, adaptively during the search process. Besides IGQ algorithms, two different mathematical modeling techniques. One of these techniques is the constraint programming (CP) model, which is known to work well with scheduling problems. The other technique is the mixed integer linear programming (MILP) model, which provides the mathematical definition of the problem. The introduction of these mathematical models supports the validation of IGQ algorithms and provides a comparison between different exact solution methodologies. To measure and compare the performance of IGQ algorithms and mathematical models, extensive computational experiments have been performed on both small and large VRF benchmarks available in the literature. Computational results and statistical analyses indicate that IGQ algorithms generate substantially better results when compared to non -learning IG algorithms. (c) 2024 Growing Science Ltd. All rights reserved.Engineering, Industrial || Managemen
Are we really addressing the roadblocks to adoption of renewable and sustainable energy technologies? Total interpretive structural modeling approach
No full textUrban areas serve as a vital contribution to the global structural change towards renewable and sustainable energy technologies which also influence climate change. The aim of this paper is to identify the adoption roadblocks to renewable and sustainable urban energy technologies. This research has three parts: a mini-systematic literature study was conducted to identify the most prevalent roadblocks. Using total interpretive structural modeling (ISM), the relationships between the roadblocks and the source of causation were then examined. The roadblocks are classified based on their dependence and driving powers using MICMAC analysis in the third part of this research. The principal results and major conclusions demonstrate that all roadblocks are necessary for renewable and sustainable urban energy technologies. The roadblocks at level I are insufficient infrastructure, lack of coordination among authorities, lack of quality and reliable data and information, and competition with non-renewable technologies || roadblocks in level II are lack of skilled and trained personnel, limited public participation, awareness, and consumer interest, and lack of standardized technology || roadblock in level III is high initial investment cost || and lastly, roadblocks in level IV are lack of subsidies and financial support programs and absence of coherent related policies. Furthermore, as a result of the MICMAC analysis, none of the aforementioned roadblocks are classified as autonomous variables, implying that they are all required. The dependent roadblocks to renewable and sustainable energy technologies are defined as lack of coordination among authorities, lack of information, and competition with non-renewable technologies. Moreover, linkage roadblocks have high dependence and driving powers which are insufficient infrastructure, limited awareness and consumer interest, and lack of standardized technology. Lastly, high initial investment costs, lack of subsidies and financial support programs, absence of coherent related policies, and lack of skilled and trained personnel are the driving roadblocks with high driving power however not dependent.Environmental Science
Architectural space classification considering topological and 3D visual spatial relations using machine learning techniques
No full textThe paper presents a novel method for classifying architectural spaces in terms of topological and visual relationships required by the functions of the spaces (where spaces such as bedrooms and bathrooms have less visual and physical relationships due to the privacy, while common spaces such as living rooms have higher visual relationship and physical accessibility) through machine learning (ML). The proposed model was applied to single and two-storey residential plans from the leading architects of the 20th century Among the five different ML models whose performances were evaluated comparatively, the best results were obtained with Cascade Forward Neural Networks (CFNN), and the average model success was calculated as 93%. The features affecting the classification models were examined based on SHAP values and revealed that width, control, 3D visibility and 3D natural daylight luminance were among the most influential. The results of five different ML models indicated that the use of topological and 3D visual relationship features in the automated classification of architectural space function can report very high levels of classification accuracy. The findings show that the classification model can be an important part of developing more efficient and adaptive floor plan design, building management and effective reuse strategies.Construction & Building Technolog
Time and frequency-based effect of energy-related R&D investments on power sector CO2 emissions: evidence from leading R&D investing countries by WLMC approach
No full textEnvironmental pollution has become highly important for countries and societies because climate change and global warming are stimulated by increasing carbon dioxide (CO2) emissions. Hence, all related parties have been searching for solutions. Considering the high role of energy use in causing CO2 emissions, energy-related research and development (R&D) investments are considered a strategic tool to curb the emissions. Accordingly, the study analyzes the effect of energy-related R&D investments on power sector CO2 emissions. In doing so, the study examines leading R&D investing countries (namely, Canada-CAN || Switzerland-CHE || Germany-DEU || France-FRA || Japan-JPN || Norway-NOR || United States-USA), considering three R&D investment sub-types (i.e., energy efficiency R&D investments-EEF || renewable energy R&D investments-RRD || nuclear energy R&D investments-NRD), uses data from 1985/Q1 to 2022/Q4, and performs Wavelet Local Multiple Correlation (WLMC) approach to analyze over times and frequencies. The results show that (i) the effects of R&D investments are weak (strong) at lower (higher) frequencies || (ii) the effects of R&D investments vary based on times, frequencies, and countries || (iii) the most dominant R&D type is EEF (CHE, DEU, FRA, & JPN), RRD (CAN & NOR), and NRD (USA) || (iv) there is an important externality among R&D types. Thus, the findings reveal the time, frequency, and country-based varying effect of R&D investments on power sector CO2 emissions implying a need for comprehensively balanced planning for R&D investments. Hence, the countries should take the highly effective R&D investment types in combating power sector CO2 emissions, allocate further budget to the effective ones, and re-consider the budget distribution among the R&D types.Environmental Science
Sofalizing and its relationship with social media addiction and psychosocial factors: A new phenomenon among emerging adults
No full textSofalizing is a term that emerged from the combination of the words 'sofa' and 'socializing', and can be defined as interacting with others online from home rather than going out and actually meeting individuals. In the present study, the relationships between psychosocial factors (including social anxiety and social connectedness) and sofalizing were examined. Additionally, the possible mediating role of social media addiction between social anxiety and connectedness with sofalizing was also investigated. The participants comprised 666 university students (69% female, Mage = 20.35 years, SD = 2.28, age range = 17 to 40 years) recruited via convenience sampling. The data were analyzed using exploratory and confirmatory factor analyses, correlation analysis, t-tests, and structural equation modeling. Results showed that social anxiety, but not social connectedness, was indirectly significantly associated with sofalizing via social media addiction. Social media addiction also had a moderate effect on sofalizing. The present study is the first to empirically explore the concept of 'sofalizing' and its potential contributing factors, and suggests that sofalizing warrants further examination of its impact on mental health and wellbeing.Social Sciences, Interdisciplinar
Enhancing e-grocery order fulfillment: improving product availability, cost, and emissions in last-mile delivery
No full textThis paper studies e-grocery order fulfillment policies by leveraging both customer and e-grocery-based data. Through the utilization of historical purchase data, product popularity trends, and delivery patterns, allocation strategies are informed to optimize performance metrics such as fill rate, carbon emissions, and cost per order. The study aims to conduct a sensitivity analysis to identify key drivers influencing these performance metrics. The results highlight that fulfillment policies optimized with the utilization of the mentioned data metrics demonstrate superior performance compared to policies not informed by data. These findings underscore the critical role of integrating data-driven models in e-grocery order fulfillment. Based on the outcomes, a grocery allocation policy, considering both proximity and product availability, emerges as promising for simultaneous improvements in several performance metrics. The study recommends that e-grocery companies leverage customer data to design and optimize delivery-oriented policies and strategies. To ensure adaptability to new trends or changes in delivery patterns, continual evaluation and improvement of e-grocery fulfillment policies are emphasized.Business || Managemen
A constraint programming approach to a real-world workforce scheduling problem for multi-manned assembly lines with sequence-dependent setup times
No full textFor over five decades, researchers have presented various assembly line problems. Recently, assembly lines with multiple workers at each workstation have become very common in the literature. These lines are often found in the manufacturing of large vehicles, where workers at a workstation may perform their assigned tasks at the same time. Most research on multi-manned assembly lines focuses on balancing tasks and workers among workstations and scheduling tasks for workers. This study, however, concentrates on assigning tasks to workers already assigned to a specific workstation, rather than balancing the entire line. The problem was identified through an industrial case study at a large vehicle manufacturing company. The study presents two methods, one using mixed integer linear programming and the other using constraint programming, to minimise the number of workers required on a multi-manned assembly line with sequence-dependent setup times. The results of the computational experiments indicate that the constraint programming method performs better than the mixed integer linear programming method on several modified benchmark instances from the literature. The constraint programming model is also tested on the real-world scenario of our industrial case study and leads to significant improvements in the productivity of the workstations.Engineering, Industrial || Engineering, Manufacturing || Operations Research & Management Scienc