Decision Making in Manufacturing and Services
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ISSN 1896-8325
e-ISSN: 2300-7087
Issue Date
2020
Volume
Vol. 14
Number
No. 2
Description
Journal Volume
Decision Making in Manufacturing and Services
Vol. 14 (2020)
Projects
Pages
Articles
Improving fishery management models and methods
(AGH University of Science and Technology Press, 2020) Arnarson, Ingólfur; Páll Jensson
For nearly six decades, fishery managers and policy makers have used bio-economic models and methods as the foundation for their management schemes. These models and methods are for the most part based on the deductive methodology of economics where central assumptions are the metaphors of »equilibrium« and »bio-economic equilibrium«. Models based on equilibrium theories are usually deterministic and static whereas the dynamics of the operations and the markets are a meager part of the problem. Less attention has been offered to inductive reasoning and modeling within the field of fishery management. The inductive method of reasoning is often based on facts and actual observations within the industries, a methodology widely used by engineers and the field of business administration. In this paper, we introduce and integrate the concept of substitutability of economic resources into a traditional bio-economic model. The results show that fishery management, which bases decisions solely on traditional bio-economic models where the dynamics and consequences of the operational decision processes of the industry are ignored, may reach decisions that work in opposition to their intended one.
A cooperation platform for distributed manufacturing
(AGH University of Science and Technology Press, 2020) Pietroń, Roman
The aim of the paper is to analyse contemporary trends in distributed manufacturing (DM) research and to present a concept to develop and test some task allocation, planning and scheduling algorithms for DM network organisations. Some concepts to identify key factor criteria and reasoning policies and rules for production/manufacturing decision support system are also undertaken. And finally, an aim is to draw a proposal for a development of a prototype decision support system with necessary communication and knowledge oriented modules to be implemented in an example of dynamic, DM and logistics network structure, particularly for very popular dynamic cluster forms in Poland. The developed concept of the organization of a multi-entity DM network will enable business-effective use of the system, supporting manufacturing decision making, consulting and offering information services in the control centre (the so-called Competence Centre) by constructing virtual reality and access to services in a distributed network of cloud computing type. Integration of the whole system into one information system will enable analysis and network resource optimization of manufacturing and logistics processes, new analytical functions, reduction of delays in the manufacturing system, management of changes and risks, and visualization of the current state of the DM system.
The role of the team in project implementation
(AGH University of Science and Technology Press, 2020) Peszko, Agnieszka
This paper intends to debate the importance of a team in successful project management. We discuss selected methodologies and pay special attention to the decision-making process in teams using traditional and agile approaches. The methods used in this article are the analysis and synthesis of the literature, as well as the results of carried out researches. To fulfill the aim of this study, we briefly characterize traditional and agile methodologies of project management, describe the team building process and define the desired competences of the team members. We also explore the differences in the decision-making process resulting from the methodology of project management selected. Additionally, we also analyze the result of research on the role of a team in the project management process. Regardless of the methodology adopted, it is crucial to not only consider the candidates' knowledge or experience while selecting project team members, but also their personality traits and interpersonal skills (social skills). However, it should be pointed out that given the specific nature of the agile methodologies, the social skills of team members are incredibly important, perhaps even more important than professional competences. In the case of traditional methodologies, teams of highly qualified specialists able to make quick and independent decisions are more efficient. In agile methodologies, the decision-making power of the project team is much greater. As the decisions are often made collectively, the executive managers' trust in the project team is of vital importance.
An assignment heuristic for time-dependent periodic routing problems with complex constraints
(AGH University of Science and Technology Press, 2020) Śliwiński, Tomasz
Periodic routing and scheduling is of the utmost importance in many industries with mobile personnel working in the field: sales representatives, service technicians, suppliers, etc. In many cases, the long-term stability of the customer to salesman assignment is required, leading to the decomposition of the major problem into single salesman subproblems. The paper addresses the assignment of customers to salesmen for the future services performed in a periodic fashion. It can be seen as the decomposition phase of the periodic vehicle routing problem PVRP into a number of Periodic Traveling Salesman Problems (PTSP). The proposed algorithm seeks the best assignment by taking into account diverse system requirements, constraints and expected operational costs including time windows, time-dependent travel times and costs, and labor laws.
Credit risk management using automatic machine learning
(AGH University of Science and Technology Press, 2020) Gaweł, Bartłomiej; Paliński, Andrzej
The article presents the basic techniques of data mining implemented in typical commercial software. They were used to assess the risk of credit card debt repayment. The article assesses the quality of classification models derived from data mining techniques and compares their results with the traditional approach using a logit model to assess credit risk. It turns out that data mining models provide similar accuracy of classification compared to the logit model, but they require much less work and facilitate the automation of the process of building scoring models.