This paper focuses on earliness and tardiness minimisation of a special case of single machine scheduling problem with common fuzzy due-date. The problem arises from a cable manufacturing system where cables are produced in different sizes and colours. The problem is generalised by considering two attributes for each product (job) and different levels for each attribute. Setup time between a pair of jobs is different when the level of one attribute or both attributes is changed, as is the case in this study. Three hybrid greedy algorithms and a genetic algorithm are introduced to solve the test problems generated for the generalised problem while Taguchi experimental design method is used to find the best level of parameters for each algorithm. Finally, the comparisons are employed to select the best method.

Turkey is one of the most suitable countries for solar power plants, owing to its ideal location in terms of receiving solar radiation; accordingly, plans are in place to expand its solar power plant system to fulfill the increasing energy demand. In this study, a combination of multicriteria decision-making and fuzzy logic was used to evaluate potential locations (cities in southern Turkey) to install new solar power plants subject to different criteria of an uncertain nature. The proposed methodology has several attractive features, which are described throughout this study. The criteria were selected based on the literature and the opinions of experts. In addition, a new criterion (capacity of existing solar power plants) was added to achieve more precise results. Ten criteria and eighteen cities were selected to form the decision matrix for the problem. First, the weight of each criterion was computed by stepwise weight assessment ratio analysis (SWARA). Then, the TOPSIS approach was extended to the Pythagorean fuzzy form in ranking the locations of the decision matrix as a new solution procedure. The results show that the best candidate city to install a new solar power plant is Antalya, followed by Karaman and Malatya as the second and third best candidates, respectively. Finally, to measure the impact of the changes in the weight of the criteria, a sensitivity analysis was conducted. Multiple scenarios were considered, and the results indicated that Antalya was the best alternative in most of the scenarios.

In this study, a typical Grey–Taguchi method has been applied in order to select the optimal configuration of a solar air heater to achieve optimum performance. The analysis is performed for different system configurations in terms of collector type, mass flow rate, and cover type. The Grey–Taguchi method, which requires the minimum possible numbers of the demanded experiments for accomplishing a robust statistical decision for a given experimental problem, has been employed, and temperature difference and thermal performance have been used as the two main criteria. It is found that by considering the temperature difference criterion, at a mass flow rate of 0.011 kg/s, the best configuration is the double-pass solar collector owning a one-fourth pierced Plexiglas cover with a distance of 60 mm between the centers of the holes. On the other hand, by considering the thermal performance as the criterion, the best configuration at a mass flow rate of 0.032 kg/s is found to be the double-pass solar collector holding a half-pierced Plexiglas cover and a distance of 60 mm distance between the centers of the holes. Finally, once both factors are taken into consideration, the optimal configuration suggested by the method is the double-pass collector with a one-quarter pierced Plexiglas cover. The method also suggests keeping a 30 mm distance between the centers of the holes and applying 0.032 kg/s of the mass flow rate to achieve the highest performance.

Purpose: This study aims to apply statistical process control (SPC) techniques to improve the quality and efficiency of the processes in a restaurant. Design/methodology/approach: SPC tools such as check sheet, cause-and-effect analysis, Pareto chart, control charts and SERVQUAL methodology is adapted to measure and improve the quality of the system. Findings: At the end, some suggestions for improving the quality of service system are proposed in this study to complete the research. Research limitations/implications: The most difficult part of this study was data collection. Because of the situation of the restaurant, the number of customers does not exceed 60 every day. Another limitation of this study is that the samples have been collected from the same population each day, and it may affect the final result. Practical implications: The research is based on the present service system at a restaurant, located at a university campus in Cyprus. Social implications: A similar study can be applied in the social sector to evaluate and improve service quality. Originality/value: In this paper, for the first time, SPC and SERVQUAL are used to evaluate and improve quality in the service sector.