PROJECT TEAM IN PROJECT MANAGEMENT METHODOLOGIES

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

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.

Improving Fishery Management Models and Methods

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

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.

Credit Risk Management Using Automatic Machine Learning

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.

Impact of government policies on Sustainable Petroleum Supply Chain (SPSC): A case study – Part I (Models)

Environmental concerns and energy security have led governments to establish legislations to convertConventional Petroleum Supply Chain (CPSC) to Sustainable Petroleum Supply Chain (SPSC). The United States(US), one of the biggest oil consumers in the world, has created regulations to manage ethanol production and con-sumption for the last half century. Though these regulations have created new opportunities, they have also added newburdens to the obligated parties. It is thus key for the government, the obligated parties, and related businesses to studythe impact of the policies on the SPSC. We develop a two-stage stochastic programming model, General Model (GM),which incorporates Renewable Fuel Standard 2 (RFS2), Tax Credits, Tariffs, and Blend Wall (BW) to study the policyimpact on the SPSC using cellulosic ethanol. The model, as any other general model available in the literature, makesit highly impractical to study the policy impact due to the model’s computational complexity. We use the GM to derivea Lean Model (LM) to study the impact by running computational experiments more efficiently and consequently byarriving at robust managerial insights much faster. We present a case study of the policy impact on the SPSC in theState of Nebraska using the LM in the accompanying part II (Ghahremanlou and Kubiak 2020).

The Application of genetic algorithms for the selection of WSE companies in Warsaw for the investment portfolio.

Portfolio analysis is a tool particularly intended for investors. Risk assessment and risk specification make the investor able to properly diversify and offset the portfolio. Broadly speaking, there are multiple tools destined for building up an efficient set of portfolios.One of them is Markowitz’s model theory postulating building up a portfolio determined on the basis of equilibrium between expected profit level as well as accepted level of risk assessment.In the context of this paper, the objective is to shed some light on creating investment portfolios based on either Markowitz's portfolio theory or evolutionary algorithm. The simulation based methods for building up a portfolio of approximately 40-50 companies listed out in the primary marketof the Warsaw Stock Exchange using the selection function proposed in the BA thesis were presented.Portfolio profit values have been evaluated in a dynamically shifted time window. The conducted analysis showed shifts in the economy at certain periods of time. The implemented genetic algorithms smoothly handled the optimization with a relatively short processing time of the task result.

Modelling & Simulation as a Strategic Tool for Decision-Making Process: A Dairy Case Study

The Dairy Industry faces many challenges compared to other sectors. On the supply side due to the nature of the raw material, large inventories are not applied; during the manufacturing process, the continuous production is highly sensitive to any sort of unplanned disruption; and on the demand side, the market dictates the commodity prices. In response to the growth in competition, dairy organizations’ strategy must incorporate technology into their daily processes in order to become more efficient, profitable and sustainable. To achieve desired levels of improvement, Modelling and Simulation has been increasing in popularity in the decision-making process. Using a Dairy company as a case study, this paper has highlighted the potential for Modelling and Simulation to be used as a powerful strategic tool for decision-making processes.

Impact of government policies on Sustainable Petroleum Supply Chain (SPSC): A case study – Part II (The State of Nebraska)

The accompanying part I (Ghahremanlou and Kubiak 2020) developed the Lean Model (LM), a two-stage stochastic programming model which incorporates Renewable Fuel Standard 2 (RFS2), Tax Credits, Tariffs, and Blend Wall (BW), to study the policy impact on the Sustainable Petroleum Supply Chain (SPSC) using cellulosic ethanol. The model enables us to study the impact by running computational experiments more efficiently and consequently by arriving at robust managerial insights much faster. In this paper, we present a case study of the policy impact on the SPSC in the State of Nebraska using the model. The case study uses available real-life data. The study shows that increasing RFS2 does not impact the amount of ethanol blended with gasoline but it might lead to bankruptcy of the refineries. We recommend that the government consider increasing the BW because of its positive economic, environmental and social impacts. For the same reason, we recommend that the tax credit for blending the US produced ethanol with gasoline be at least 0:189 $/gal and the tariff for imported ethanol be at least 1:501 $/gal. These also make the State independent from foreign ethanol thereby enhancing its energy security. Finally, the change in policy impacts the SPSC itself, most importantly it influences the strategic decisions, however setting up a bio-refinery at York county and a blending site at Douglas county emerge as the most robust location decisions against the policy change in the study.

Simulation of the Impact of Waste Batteries on Ecosystem Reliability

To assess the impact of not just the battery as such but its multi-element composition on the state of the environment, a new approach is proposed through the determination of the reliability of ecosystems, which makes it possible to obtain quantitative indexes of the stability and losses of natural ecosystems. These data can be used as indicators of the state of the environment, and hence as the assessment of an environmental component that is important for determining the actual impact of the multi-element composition of batteries. On the basis of such indicators, which can be obtained using the SimaPro software, it is possible to calculate thresholds beyond which negative phenomena occur, as well as to predict and simulate situations, to carry out the mapping of sources of risks, to monitor changes, and this will allow identifying the causes of these changes or determining the factors that slow down or retard the approach of ecosystems to a critical state, i.e. to develop preventive measures to avoid disasters. The eco-indicator 99 is one of the methods that allows us to accept one estimate for the whole product - the so-called ecological index. It is the sum of all individual eco-points or partial indexes for all life-cycle processes. The computational procedure is carried out by summing up the results of weighing the phases of the life cycle.