Improving Software Development Processes with Multicriteria Methods

All software development processes include steps where several alternatives induce a choice, a decision-making. Sometimes, methodologies offer a way to make decisions. However, in a lot of cases, the arguments to carry out the decision are very poor and the choice is made in an intuitive and hazardous way. The aim of our work is to offer a scientifically founded way to guide the engineer through tactical choices with the application of multicriteria methods in software development processes. This approach is illustrated with three cases: risks, use cases and tools within Rational Unified Process.Comment: 11 page

Improving the quality of the industrial enterprise management based on the network-centric approach

The article examines the network-centric approach to the industrial enterprise management to improve the ef ciency and effectiveness in the implementation of production plans and maximize responsiveness to customers. A network-centric management means the decentralized enterprise group management. A group means a set of enterprise divisions, which should solve by joint efforts a certain case that occurs in the production process. The network-centric management involves more delegation of authority to the lower elements of the enterprise’s organizational structure. The industrial enterprise is considered as a large complex system (production system) functioning and controlled amidst various types of uncertainty: information support uncertainty and goal uncertainty or multicriteria uncertainty. The information support uncertainty occurs because the complex system functioning always takes place in the context of incomplete and fuzzy information. Goal uncertainty or multicriteria uncertainty caused by a great number of goalsestablished for the production system. The network-centric management task de nition by the production system is formulated. The authors offer a mathematical model for optimal planning of consumers’ orders production with the participation of the main enterprise divisions. The methods of formalization of various types of uncertainty in production planning tasks are considered on the basis of the application of the fuzzy sets theory. An enterprise command center is offered as an effective tool for making management decisions by divisions. The article demonstrates that decentralized group management methods can improve the ef ciency and effectiveness of the implementation of production plans through the self-organization mechanisms of enterprise divisions.The work has been prepared with the financial support from the Russian Ministry of Education and Science (Contract No. 02.G25.31.0068 of 23.05.2013 as part of the measure to implement Decision of the Russian Government No. 218)

Open source environment to define constraints in route planning for GIS-T

Route planning for transportation systems is strongly related to shortest path algorithms, an optimization problem extensively studied in the literature. To find the shortest path in a network one usually assigns weights to each branch to represent the difficulty of taking such branch. The weights construct a linear preference function ordering the variety of alternatives from the most to the least attractive.Postprint (published version

Land suitability analysis for emerging fruit crops in central Portugal using GIS

Fruit production is an important component of agricultural production in Portugal, and it has a positive impact on the economy, especially in rural areas. In recent years, there has been increased investment in so-called ‘emerging crops’. It is agreed that using the crops that are best suited to the soil and climate conditions as well as the socio-economic environment promotes sustainable use in rural areas. The objective of this study is to determine the suitability of different emerging fruit crops for cultivation in the Beira Baixa region based on analysis of soil and climate factors. The pistachio tree (Pistacia vera L.), strawberry tree (Arbutus unedo L.), almond tree (Prunus dulcis (Mill.) DA Webb) and walnut tree (Juglans regia L.) were checked against the biophysical criteria for cultivation. The results were processed using a geographic information system. Analysis was performed using the analytical hierarchy process (AHP). Thus, after dividing the problem into hierarchical levels of decision-making, a pairwise comparison of criteria was performed to evaluate the weights of these criteria based on a scale of importance. Then, the consistency of these operations was validated. The AHP was adequate for evaluation of fruit tree species’ suitability since it enabled integration of several criteria, decision-making and problem resolution. It is essential to be aware of the suitability and resilience of new crops in order to meet the need to adapt to climate change.info:eu-repo/semantics/publishedVersio

Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future.

Treatment planning is an essential step of the radiotherapy workflow. It has become more sophisticated over the past couple of decades with the help of computer science, enabling planners to design highly complex radiotherapy plans to minimize the normal tissue damage while persevering sufficient tumor control. As a result, treatment planning has become more labor intensive, requiring hours or even days of planner effort to optimize an individual patient case in a trial-and-error fashion. More recently, artificial intelligence has been utilized to automate and improve various aspects of medical science. For radiotherapy treatment planning, many algorithms have been developed to better support planners. These algorithms focus on automating the planning process and/or optimizing dosimetric trade-offs, and they have already made great impact on improving treatment planning efficiency and plan quality consistency. In this review, the smart planning tools in current clinical use are summarized in 3 main categories: automated rule implementation and reasoning, modeling of prior knowledge in clinical practice, and multicriteria optimization. Novel artificial intelligence-based treatment planning applications, such as deep learning-based algorithms and emerging research directions, are also reviewed. Finally, the challenges of artificial intelligence-based treatment planning are discussed for future works

Towards the adoption of technological innovations: decision processes in transport policy definition

The widespread of technological innovations is rapidly changing the way modern societies are organized. Such phenomenon highly affects the economy of most developed countries (and, more recently, of developing countries, too), influencing work organization and habits. Besides, technological innovations modify the way in which transport systems are organized, by introducing new transport solutions as well as by upgrading the performances of the existing transport systems, in accordance to a more efficient organization. Several tools have been designed to predict the effects of the adoption of technological innovations in transport. The aim of this paper is to deal with the decision processes involved in the definition of the transport policies for the introduction of such technological solutions. To do this the way in which the new transport solutions affect the local context is analysed. In particular, this work aim to identify the most relevant attributes which influence the decision processes on the adoption of such technological solutions, with reference to their impact on the territory and on the economic activities. To do this, the analysis focuses on the effects involved by the use of wireless technologies and radio frequency identification into seaport infrastructures. Such technologies enable an easier identification of goods in transport terminals; this implies advantages in the organization of the terminal activities, allowing lower time and costs for handling, and at the same time it ensures a greater compliance to security requirements, thus upgrading the level of the performances in these transport systems. On the other hand, the effects of the improvements in transport systems affect the economic context in which transport infrastructures are set. Thus, the adoption of such a technological innovation can represent the chance for local development of the region, due to the better performances of the transport system and to the consequent increased territorial accessibility.

Analysis of the potentials of multi criteria decision analysis methods to conduct sustainability assessment

Sustainability assessments require the management of a wide variety of information types, parameters and uncertainties. Multi criteria decision analysis (MCDA) has been regarded as a suitable set of methods to perform sustainability evaluations as a result of its flexibility and the possibility of facilitating the dialogue between stakeholders, analysts and scientists. However, it has been reported that researchers do not usually properly define the reasons for choosing a certain MCDA method instead of another. Familiarity and affinity with a certain approach seem to be the drivers for the choice of a certain procedure. This review paper presents the performance of five MCDA methods (i.e. MAUT, AHP, PROMETHEE, ELECTRE and DRSA) in respect to ten crucial criteria that sustainability assessments tools should satisfy, among which are a life cycle perspective, thresholds and uncertainty management, software support and ease of use. The review shows that MAUT and AHP are fairly simple to understand and have good software support, but they are cognitively demanding for the decision makers, and can only embrace a weak sustainability perspective as trade-offs are the norm. Mixed information and uncertainty can be managed by all the methods, while robust results can only be obtained with MAUT. ELECTRE, PROMETHEE and DRSA are non-compensatory approaches which consent to use a strong sustainability concept, accept a variety of thresholds, but suffer from rank reversal. DRSA is less demanding in terms of preference elicitation, is very easy to understand and provides a straightforward set of decision rules expressed in the form of elementary “if … then …” conditions. Dedicated software is available for all the approaches with a medium to wide range of results capability representation. DRSA emerges as the easiest method, followed by AHP, PROMETHEE and MAUT, while ELECTRE is regarded as fairly difficult. Overall, the analysis has shown that most of the requirements are satisfied by the MCDA methods (although to different extents) with the exclusion of management of mixed data types and adoption of life cycle perspective which are covered by all the considered approaches

Incorporating stakeholders’ knowledge in group decision-making

International audienc