Decision Making in Manufacturing and Services

Improving Fishery Management Models and Methods

2021-01-27T17:17:17+01:00

In a dynamic, environment, the decision makers make use of many different resources where two or more can act as substitutes. At each decision moment in time, the market prices will be constant, and the relative prices of accessible resources will determine the economic rationale of the process. Ignoring or downplaying the effects of substitutability of resources in dynamic economic processes may lead to mismanagement of the fish stocks and result in serious economic consequences for the respective fishing industries.

For nearly five decades’ fishery managers and policy makers have used bio-economic models and methods as foundation for their management schemes. These models and methods are for the most 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 where dynamics of 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 opposite of their intention.

Cooperation platform for distributed manufacturing

2021-01-27T17:17:19+01:00

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.

Project Team in Project Management Methodologies

2021-01-27T17:17:20+01:00

The specific nature of project management causes that the selection of the right people to join the project team has become crucial to the success of any project. The present study aims at showing the role of a well-chosen project team in the project management regardless of whether the project is run according to traditional or agile methodologies. Special attention has been paid to the decision making process in project team with the use of traditional and agile methodologies. In case of traditional, classical methodologies, more efficient are teams of highly qualified specialists, which are able to make decisions, more often individual ones, as quickly as possible and precisely. Given the fact that in agile methodologies there is greater decisiveness of the team, group decisions are made more often. Management’s confidence in project team is of vital importance in agile methodologies. In order to fulfill the aim of the study, traditional and agile methodologies for project management have been briefly characterized, the process of project team building and the results of scientific research pointing to significant role of the project team in project management have been presented. It has been stressed out that, regardless of the chosen methodology, while selecting project team members it is important to consider not only members’ knowledge or experience, but also relevant personality traits and interpersonal skills (social skills). However, it should be pointed out that given the specific nature of the agile methodologies, social skills of team members become incredibly important, and in many cases more important than professional competences.

Clustering heuristic for time-dependent periodic routing problems with complex constraints

2021-01-27T17:17:20+01:00

Periodic routing and scheduling is of utmost importance in many industries with mobile personnel working in the field: sales representatives, service technicians, suppliers, etc. The resulting optimization problems are of large scale and complexity, mostly due to discrete, combinatorial nature of the systems and due to complicated, nonuniform constraints. In many cases the long-term stability of the customer to personnel allocation is required, leading to the decomposition of the major problem into single employee subproblems.

The paper deals with building clusters of customers visited by a single salesperson. The procedure takes into account diverse system requirements and constraints, possible traveling schedules and expected operational costs. The difficulty of the problem lies in its large scale and constraints complexity as well as in troublesome objective evaluation for the given solution. The general solution concept is presented. Its usefulness is supported by the results of the computational experiments.

Credit Risk Management Using Automatic Machine Learning

2021-07-08T17:48:15+02:00

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.