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Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

Enterprise resource planning (ERP) offers a streamlined system architecture to feed businesses with beneficial information in the current intense global competition. The primary concern of ERP is how to integrate different functional units to facilitate a unified flow of information. This paper aims at providing a non-trivial practice of integrating the quality control (QC) system into the core ERP processes of a real large-scaled case study.

To satisfy the purpose of the current study, a large-scale steel making holding, inclusive of 27 business units being dispersed over a wide area, has been targeted. In our research methodology, a sample of four business units is selected as the pilot cases to be investigated at first. The output results of such investigations are further extended to the other units. In light of the investigation, the existing QC working conditions of the pilot cases are assessed through the As-Is model. The To-Be models are derived based on the best practices and the integration scope is then bordered.

The findings show that the integrated QC solution has enabled the following features: the smooth interconnection between QC and other functional units like purchase and manufacturing, the ease of generating real-time performance report of QC unit, the sack of tracing the quality of any available item in the system and the root-cause of defects, and the straightforwardness of the qualitative assessment of the suppliers.

There is almost no similar practice for designing a large-sized integrated system from scratch in the target region associated with our case study while the off-the-shelf products are prohibitively expensive.

This paper includes implications for providing a standard practice on integrating a substantial module of ERP down to the smallest detail.

The value of the current paper is associated with fulfilling a critical research gap in the context of studying the QC integration into an enterprise solution. In fact, despite the importance of the QC module and its plethora of interconnection with other functional units, the literature review shows a centric lack of considering such integration in a real case study, particularly the large-scale one. Further, this paper works as a valuable study in the literature owing to not only focusing on the design and development of an integrated QC solution but also considering the deployment facet of such a practice.

The purpose of this paper is to propose a new mixed-integer formulation for the time-dependent multi-skilled resource-constrained project scheduling problem (MSRCPSP/t) considering learning effect. The proposed model extends the basic form of the MSRCPSP by three concepts: workforces have different efficiencies, it is possible for workforces to improve their efficiencies by learning from more efficient workers and the availability of workforces and resource requests of activities are time-dependent. To spread dexterity from more efficient workforces to others, this study has integrated the concept of diffusion maximization in social networks into the proposed model. In this respect, the diffusion of dexterity is formulated based on the linear threshold model for a network of workforces who share common skills. The proposed model is bi-objective, aiming to minimize make-span and total costs of project, simultaneously.

The MSRCPSP is an non-deterministic polynomial-time hard (NP-hard) problem in the strong sense. Therefore, an improved version of the non-dominated sorting genetic algorithm II (IM-NSGA-II) is developed to optimize the make-span and total costs of project, concurrently. For the proposed algorithm, this paper has designed new genetic operators that help to spread dexterity among workforces. To validate the solutions obtained by the IM-NSGA-II, four other evolutionary algorithms – the classical NSGA-II, non-dominated ranked genetic algorithm, Pareto envelope-based selection algorithm II and strength Pareto evolutionary algorithm II – are used. All algorithms are calibrated via the Taguchi method.

Comprehensive numerical tests are conducted to evaluate the performance of the IM-NSGA-II in comparison with the other four methods in terms of convergence, diversity and computational time. The computational results reveal that the IM-NSGA-II outperforms the other methods in terms of most of the metrics. Besides, a sensitivity analysis is implemented to investigate the impact of learning on objective function values. The outputs show the significant impact of learning on objective function values.

The proposed model and algorithm can be used for scheduling activities of small- and large-size real-world projects.

Based on the previous studies reviewed in this paper, one of the research gaps is the MSRCPSP with time-dependent resource capacities and requests. Therefore, this paper proposes a multi-objective model for the MSRCPSP with time-dependent resource profiles. Besides, the evaluation of learning effect on efficiency of workforces has not been studied sufficiently in the literature. In this study, the effect of learning on efficiency of workforces has been considered. In the scarce number of proposed models with learning effect, the researchers have assumed that the efficiency of workforces increases as they spend more time on performing a skill. To the best of the authors’ knowledge, the effect of learning from more efficient co-workers has not been studied in the literature of the RCPSP. Therefore, in this research, the effect of learning from more efficient co-workers has been investigated. In addition, a modified version of the NSGA-II algorithm is developed to solve the model.