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The purpose of this paper is to survey and express the advantages and disadvantages of the existing approaches for solving grey linear programming in decision-making problems.

After presenting the concepts of grey systems and grey numbers, this paper surveys existing approaches for solving grey linear programming problems and applications. Also, methods and approaches for solving grey linear programming are classified, and its advantages and disadvantages are expressed.

The progress of grey programming has been expressed from past to present. The main methods for solving the grey linear programming problem can be categorized as Best-Worst model, Confidence degree, Whitening parameters, Prediction model, Positioned solution, Genetic algorithm, Covered solution, Multi-objective, Simplex and dual theory methods. This survey investigates the developments of various solving grey programming methods and its applications.

Different methods for solving grey linear programming problems are presented, where each of them has disadvantages and advantages in providing results of grey linear programming problems. This study attempted to review papers published during 35 years (1985–2020) about grey linear programming solving and applications. The review also helps clarify the important advantages, disadvantages and distinctions between different approaches and algorithms such as weakness of solving linear programming with grey numbers in constraints, inappropriate results with the lower bound is greater than upper bound, out of feasible region solutions and so on.

The purpose of this paper is to present a process for managing project problem‐solving patterns. It focuses on shifting the emphasis of project teams toward a more collaborative and knowledge‐based style of dealing with challenges to project performance. The methods proposed in this paper encourage project managers to integrate processes for becoming more agile by tapping into lesson learned and knowledge gained to create higher quality solutions to problems.

This paper proposes a conceptual framework for recognizing problem‐solving patterns and transforming problem solving from an individual passive event to a more open, agile active, systemic process. Several actual case examples are provided to illustrate applications.

The paper examines how taking a more open approach to problem solving in projects leads to better solutions. The proposed method and lessons from actual cases offer support to these proposals.

The proposed models in this paper originate from the conclusions and observations drawn by the authors over many years of experience. However, they are not the product of a systematic research effort. This paper is intended to provide a new lens for project managers to view projects. It does not purport to declare findings of any research or analyze any sort of research.

The conceptual framework provided in this paper is a practical one derived from the practices used in leading companies. The paper provides practical guidelines to aid project managers in recognizing and managing problem‐solving patterns to create better solutions to problems.

Modern society is plagued by the effects of ineffective problem‐solving initiatives in business, government, and not‐for‐profit organizations. Flawed proposed solutions exact a toll on organizations, their members, and the constituents they serve. This paper proposes a way of improving the quality of problem‐solving processes that may benefit a broad scale of people.

The concept of a problem‐solving pattern and a typology of problem‐solving patterns presented in this paper, provide project managers with a new way of conceiving of how problem solving can be used to improve project performance and adaptability.

Problem-solving” is the most crucial key insight of scientific research. This study focuses on constructing the “problem-solving” knowledge graph of scientific domains by extracting four entity relation types: problem-solving, problem hierarchy, solution hierarchy and association.

This paper presents a low-cost method for identifying these relationships in scientific papers based on word analogy. The problem-solving and hierarchical relations are represented as offset vectors of the head and tail entities and then classified by referencing a small set of predefined entity relations.

This paper presents an experiment with artificial intelligence papers from the Web of Science and achieved good performance. The F1 scores of entity relation types problem hierarchy, problem-solving and solution hierarchy, which were 0.823, 0.815 and 0.748, respectively. This paper used computer vision as an example to demonstrate the application of the extracted relations in constructing domain knowledge graphs and revealing historical research trends.

This paper uses an approach that is highly efficient and has a good generalization ability. Instead of relying on a large-scale manually annotated corpus, it only requires a small set of entity relations that can be easily extracted from external knowledge resources.

As a problem-solving tool, the kaizen event (KE) is underutilised in practice. Assuming this is due to a lack of group process quality during those events, the authors aimed to grasp what is needed during high-quality KE meetings. Guided by the phased approach for structured problem-solving, the authors built and explored a measure for enriching future KE research.

Six phases were used to code all verbal contributions (N = 5,442) in 21 diverse, videotaped KE meetings. Resembling state space grids, the authors visualised the course of each meeting with line graphs which were shown to ten individual kaizen experts as well as to the filmed kaizen groups.

From their reactions to the graphs the authors extracted high-quality KE process characteristics. At the end of each phase, that should be enacted sequentially, explicit group consensus appeared to be crucial. Some of the groups spent too little time on a group-shared understanding of the problem and its root causes. Surprisingly, the mixed-methods data suggested that small and infrequent deviations (“jumps”) to another phase might be necessary for a high-quality process. According to the newly developed quantitative process measure, when groups often jump from one phase to a distant, previous or next phase, this relates to low KE process quality.

A refined conceptual model and research agenda are offered for generating better solutions during KEs, and the authors urge examinations of the effects of well-crafted KE training.

Toyota's success in the automotive industry has been attributed to many factors, one of which is their systematic company‐wide problem‐solving approach. While Toyota's structured framework for thinking through problems may offer some interesting insight, it is speculated that how they develop and train their managers to share this thinking with their employees is the key to implementation. The purpose of this paper is to share these issues.

This work utilizes a new and novel technique to examine how Toyota trains and develops their managers to support problem solving. A form of data mining will be used in this research combined with Singular Value Decomposition to mathematically analyze organizational documents from Toyota.

The findings of this research show that the role of management is essential to the successful application of problem solving at Toyota. Results indicate that managers are trained to provide more intense coaching early on the front end of problem solving, specifically in step 2 problem breakdown, so that decision making and involvement of employees can occur more naturally in developing countermeasures.

This research method is solely based on mathematical and statistically analysis of organizational documents to reveal important and latent criteria critical for effectiveness.

This paper provides new insights and understanding of Toyota's 8‐step problem‐solving process. The role of management has been identified as an essential element in coaching and developing employees in the implementation of a company‐wide, systematic problem‐solving methodology.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

Although in practice it is commonly found that there are several antecedents relevant to a particular problem, only one specific event represents its real cause. Analysis of the potential causes and the identification of the single cause that ultimately relates to the problem are the crux of problem solving. Attempts to develop a systematic procedure of problem solving, named the S‐S problem‐solving method, and to apply the method to the problem of the penalty shoot‐out ‐ a decisive stage in cup competition football matches. In the World Cup 1990 semi‐finals, England lost to West Germany in a penalty shoot‐out. In an attempt to find the possible reasons for defeat by using the S‐S problem‐solving method, identifies one real cause of the problem. Two examples illustrate the significance of the method in finding the real cause of a problem.

The purpose of this research is to present the results of a recent interpretive study of 11 small Central Vancouver Island firms in British Columbia, Canada, which yield new interpretations of the nature of problem‐solving processes within the wider context of managerial capability as a critical contributor to small business survival.

The methodological approach taken is positioned within an emergent body of research in the field of small business and entrepreneurship that applies an interpretive paradigm to uncover the complex facets of how individuals develop their capabilities and management practices with a particular emphasis on the small business owner‐manager. More specifically, the critical incident technique method, along with an approach to data analysis and coding that draws from grounded theory, is combined and applied as a qualitative research strategy to yield new understandings of problem solving in small firms.

Research findings reveal the intuitive, improvised and non‐linear nature of how problems are actually solved in the sample of small firms studied, in contrast with a number of well‐known theoretical research frameworks that propose well‐defined and delineated steps in the problem‐solving process.

The small sample size and the methods chosen to conduct the research do not allow for the generalization of findings to all firms, yet do allow for the emergence of themes among the businesses that participated in the study. Research could be expanded by applying a similar research design to small firms in other regions of Canada to determine whether significant differences or similarities exist and to identify the implications for research in the area of problem solving in small firms.

The identification of problems as critical incidents represents a primary focus of the research and provides a more explanatory account of problem solving from the perspective of small firm owner‐managers involved in the process. The analysis of these highly subjective interpretations represents valuable research findings that provide a basis for the development of theory on problem solving in small firms.