KONSTANTINOS ANAGNOSTOPOULOS | Democritus University of Thrace (original) (raw)

PROJECT MANAGEMENT / SCHEDULING by KONSTANTINOS ANAGNOSTOPOULOS

Construction Management and Economics, 2010

Resource levelling techniques aim to minimize the fluctuation from one time period to another in ... more Resource levelling techniques aim to minimize the fluctuation from one time period to another in resource usage. Except for small‐sized problems, though, computational optimization procedures are inefficient when solving construction resource levelling problems. Consequently, heuristic and metaheuristic approaches are used to get an acceptable, but not necessarily optimal, solution. A simulated annealing hyperheuristic to generate better‐levelled resource profiles is proposed.

Journal of Computing in Civil Engineering, 2012

IEEE Congress on Evolutionary Computation, 2010

The resource constrained project scheduling problem is one of the most important issues that proj... more The resource constrained project scheduling problem is one of the most important issues that project managers have to deal with during the project implementation, as constrained resource availabilities very often lead to delays in project completion and budget overruns. For solving this NP-hard optimization problem, we propose a genetic based hyperheuristic, i.e. an algorithm controlling a set of low-level heuristics

Journal of Construction Engineering and Management, 2012

We present a tabu search-based hyper-heuristic algorithm for solving construction resource leveli... more We present a tabu search-based hyper-heuristic algorithm for solving construction resource leveling problems, i.e. resource leveling under resource constraints with the prescribed maximum project duration to be equal or greater than the initial/minimum duration, as well as the related resource availability cost problem. The algorithm operates within a commercial project management software package by altering the priorities assigned to activities. The hyper-heuristic controls a set of low-level heuristics, which modify the priorities of selected activities by performing simple moves such as “replace” and “swap”. The most promising heuristics according to their efficiency are applied first, and a tabu list is used to prohibit heuristics with recently poor performance from being applied too soon. The application of the algorithm in three project cases showed that the proposed procedure is promising for handling resource optimization problems.

In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic algorithm for... more In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic algorithm for solving the resource constrained project scheduling problem (RCPSP). To the best of our knowledge, this is the first attempt to develop a PSO hyper-heuristic and apply to the classic RCPSP. The hyper-heuristic works as an upper-level algorithm that controls several low-level heuristics which operate to the solution space. The solution representation is based on random keys. Active schedules are constructed by the serial scheduling generation scheme using the priorities of the activities which are modified by the low-level heuristics of the algorithm. Also, the double justification operator, i.e. a forward–backward improvement procedure, is applied to all solutions. The proposed approach was tested on a set of standard problem instances of the well-known library PSPLIB and compared with other approaches from the literature. The promising computational results validate the effectiveness of the proposed approach.

Applied Mathematics and Computation, 2010

ABSTRACT

An effective procedure for time-cost trade off in Critical Path Method (CPM) networks when discre... more An effective procedure for time-cost trade off in Critical Path Method (CPM) networks when discrete time-cost combinations are allowed on the project activities is developed. The particular problem confronted in this study is to select a time-cost combination for each activity which minimizes the project overall cost subject to a due-date. For this inherently difficult to solve problem, the heuristic algorithm constructs a feasible solution of minimal cost by compressing and increasing the duration of critical and noncritical activities. In order to improve the time efficiency of the algorithm, a subroutine is used that recalculates the critical paths by restricting the calculations to a partial network. The procedure, coded in Visual Basic and tested on a large set of randomly generated networks, has provide fairly good solutions at a small computational effort.

Project participants, through experience, have an initial perception and predisposition towards r... more Project participants, through experience, have an initial perception and predisposition towards risk and the
types of risks they are willing and able to undertake. This is equally true for parties interested in public–private
partnership (PPP) projects. These initial positions have been registered for the major Greek PPP market
stakeholders potentially involved in a PPP arrangement through a survey covering all candidate construction
companies, interested financing institutes and a number of public sector entities to be involved in PPPs.
Findings revealed that stakeholders were, for the majority of risks identified, in agreement as to preferred risk
allocation. Risk allocation preferences for construction companies were compared with similar findings for the
UK, a mature PPP market, indicating a possible learning/maturing process based on the particular country
background. Conclusions add to other surveys carried out on the subject and should enable public sector clients
to establish a more efficient framework for risk allocation, thus reducing negotiations prior to contract award
and minimizing the risk of poor risk distribution.

Operational Research, 2004

FINANCIAL ENGINEERING by KONSTANTINOS ANAGNOSTOPOULOS

This paper investigates the ability of Multiobjective Evolutionary Algorithms (MOEAs), namely the... more This paper investigates the ability of Multiobjective Evolutionary Algorithms (MOEAs), namely the Non-dominated Sorting Genetic Algorithm II (NSGA-II), Pareto Envelope-based Selection Algorithm (PESA) and Strength Pareto Evolutionary Algorithm 2 (SPEA2), for solving complex portfolio optimization problems. The portfolio optimization problem is a typical bi-objective optimization problem with objectives the reward that should be maximized and the risk that should be minimized. While reward is commonly measured by the portfolio’s expected return, various risk measures have been proposed that try to better reflect a portfolio’s riskiness or to simplify the problem to be solved with exact optimization techniques efficiently. However, some risk measures generate additional complexities, since they are non-convex, non-differentiable functions. In addition, constraints imposed by the practitioners introduce further difficulties since they transform the search space into a non-convex region. The results show that MOEAs, in general, are efficient and reliable strategies for this kind of problems, and their performance is independent of the risk function used.

We formulate the portfolio selection as a tri-objective optimization problem so as to find tradeo... more We formulate the portfolio selection as a tri-objective optimization problem so as to find tradeoffs
between risk, return and the number of securities in the portfolio. Furthermore, quantity and class
constraints are introduced into the model in order to limit the proportion of the portfolio invested in
assets with common characteristics and to avoid very small holdings. Since the proposed portfolio
selection model involves mixed integer decision variables and multiple objectives finding the exact
efficient frontier may be very hard. Nevertheless, finding a good approximation of the efficient surface
which provides the investor with a diverse set of portfolios capturing all possible tradeoffs between the
objectives within limited computational time is usually acceptable. We experiment with the current
state of the art evolutionary multiobjective optimization techniques, namely the Non-dominated
Sorting Genetic Algorithm II (NSGA-II), Pareto Envelope-based Selection Algorithm (PESA) and Strength
Pareto Evolutionary Algorithm 2 (SPEA2), for solving the mixed-integer multiobjective optimization
problem and provide a performance comparison among them using metrics proposed by the
community.

This paper compares the effectiveness of five state-of-the-art multiobjective evolutionary algori... more This paper compares the effectiveness of five state-of-the-art multiobjective evolutionary algorithms (MOEAs) together with a steady state evolutionary algorithm on the mean–variance cardinality constrained portfolio optimization problem (MVCCPO). The main computational challenges of the model are due to the presence of a nonlinear objective function and the discrete constraints. The MOEAs considered are the Niched Pareto genetic algorithm 2 (NPGA2), non-dominated sorting genetic algorithm II (NSGA-II), Pareto envelope-based selection algorithm (PESA), strength Pareto evolutionary algorithm 2 (SPEA2), and e-multiobjective evolutionary algorithm (e-MOEA). The computational comparison was performed using formal metrics proposed by the evolutionary multiobjective optimization community on publicly available data sets which contain up to 2196 assets.

Managerial Finance, 2010

Purpose – The purpose of this paper is to present a procedure for finding the efficient frontier,... more Purpose – The purpose of this paper is to present a procedure for finding the efficient frontier, i.e. a non-decreasing curve representing the set of Pareto-optimal or non-dominated portfolios, when the standard Markowitz' classical mean-variance model is enriched with additional constraints. Design/methodology/approach – The mean-variance portfolio optimization model is extended to include integer constraints that limit a portfolio to have

International Journal of Financial Markets and Derivatives, 2011

ENVIRONMENTAL MANAGEMENT by KONSTANTINOS ANAGNOSTOPOULOS

Regarding the inability to fulfill regional landfill demands, the inefficiency of municipal solid... more Regarding the inability to fulfill regional landfill demands, the inefficiency of municipal solid waste management systems due to shortages of suitable and efficient infrastructures remains a crucial social issue. In addition, the fact that there are numerous environmental, social, and design factors that need to be taken into account by decision makers (DMs) raises serious concerns regarding the task of identifying appropriate sites for municipal solid waste landfills. For this reason, the use of multicriteria spatial decision support systems, the synergic combination of geographic information system (GIS) and multicriteria decision analysis (MCDA) methods, is proposed, taking into consideration the spatial nature of the problem and the need to incorporate conflicting objectives and DM preferences. The paper at hand proposes a framework that enables the implementation of the measuring attractiveness by a categorical based evaluation technique (MACBETH) method in GIS-based raster-driven suitability analysis. MACBETH is a well-established MCDA method for the evaluation of alternative actions/scenarios based on qualitative judgments regarding their attractiveness to a DM. A real-world case study concerning the placement of a landfill in the region of Thrace, northeastern Greece, is discussed in detail. The computational part of the MACBETH method is supported by the M-MACBETH decision support system. The proposed framework consists of an attempt that allows MACBETH implementation in GIS-based raster-driven suitability analysis. In addition, a comparative analysis with other well-known methods was conducted showing that the proposed framework produces sufficient results.

The identification of sites for locating new natural systems for wastewater treatment (NSWT), suc... more The identification of sites for locating new natural systems for wastewater treatment (NSWT), such as stabilization ponds and constructed wetlands, should combine multiple crucial factors (environmental, design, social and economic), and thus the implementation of multicriteria decision-making (MCDM) methods is required. In addition, the spatial nature of the site selection process necessitates the use of geographic information systems (GISs) because they are unanimously recognized as the most appropriate tool capable of supporting sophisticated spatial decision making. The resulting multicriteria spatial decision support systems (MC-SDSSs) provide a consistent framework for dealing with conflicting objectives while integrating the decision makers' (DMs') preferences in spatially related patterns/problems. A map-based, interactive UTAII implementation is presented, which provides a link between a well-understood decision support method and exploratory geographic visualization. Spatial UTA (S-UTA) is applied in a real case study concerning the ranking of candidate sites for implementing natural systems for wastewater treatment in the Evros–Rodopi prefectures of northeastern Greece. Finally, the obtained results are compared with those derived using other MCDM approaches to evaluate the performance of S-UTA in GIS-based land use suitability analyses.
Publication Date: May 3, 2013
Publication Name: Journal of Environmental Management

When decentralized strategies are considered for managing wastewater, natural systems for wastewa... more When decentralized strategies are considered for managing wastewater, natural systems for wastewater treatment (NSWT) (constructed wetlands) seem to be strongly preferred in comparison with the conventional activated sludge wastewater treatment systems. However, because of their high land requirements, land-use suitability analysis should be conducted to specify adequate areas for their accommodation. Multicriteria spatial decision support systems have emerged as the technology that takes into account both decision criteria and constraints in complex land-use planning problems. This study presents a multiattribute decision analysis approach called the spatial fuzzy Analytic Hierarchy Process (SFAHP) to support raster-based land-use suitability studies for the implementation of NSWT. The SFAHP enables decision makers to circumvent vagueness when they perform evaluations using linguistic variables. Its application in a region of Northeastern Greece using a two-level criteria hierarchical model demonstrates its potential use for suitability analyses.

Three alternative irrigation projects for the East Macedonia-Thrace Region, Greece, are considere... more Three alternative irrigation projects for the East Macedonia-Thrace Region, Greece, are considered. Given
the presence of valuable natural ecosystems in the area, environmental considerations are of great importance.
In order to evaluate the projects, a fuzzy multicriteria benefit–cost approach is proposed. The
overall goal is the rational management of water resources, and the projects appraisal is based on economic,
social, and environmental criteria. Alternative scenarios on the availability of water resources are
also incorporated in the decision model. The decision problem is formulated as two hierarchies, and the
projects are ranked according to the benefit–cost ratio of their global priorities. The proposed method
is proved to be, on the one hand, very suitable when both costs and benefits cannot be easily expressed
into monetary terms as the traditional benefit–cost analysis requires; and, on the other hand, a valuable
tool to cope with vague judgments.

Operational Research, 2010

Renowned for their ability to deal with spatial problems, commercial GIS software packages can pl... more Renowned for their ability to deal with spatial problems, commercial GIS software packages can play crucial role in spatial decision making processes, provided that they have tools that allow both private and public organizations to manage and analyze spatial referenced data. In particular, land-use suitability analysis applications are valuable, where the use of conflicting objectives and decision maker’s (DMs) preferences

Construction Management and Economics, 2010

Resource levelling techniques aim to minimize the fluctuation from one time period to another in ... more Resource levelling techniques aim to minimize the fluctuation from one time period to another in resource usage. Except for small‐sized problems, though, computational optimization procedures are inefficient when solving construction resource levelling problems. Consequently, heuristic and metaheuristic approaches are used to get an acceptable, but not necessarily optimal, solution. A simulated annealing hyperheuristic to generate better‐levelled resource profiles is proposed.

Journal of Computing in Civil Engineering, 2012

IEEE Congress on Evolutionary Computation, 2010

The resource constrained project scheduling problem is one of the most important issues that proj... more The resource constrained project scheduling problem is one of the most important issues that project managers have to deal with during the project implementation, as constrained resource availabilities very often lead to delays in project completion and budget overruns. For solving this NP-hard optimization problem, we propose a genetic based hyperheuristic, i.e. an algorithm controlling a set of low-level heuristics

Journal of Construction Engineering and Management, 2012

We present a tabu search-based hyper-heuristic algorithm for solving construction resource leveli... more We present a tabu search-based hyper-heuristic algorithm for solving construction resource leveling problems, i.e. resource leveling under resource constraints with the prescribed maximum project duration to be equal or greater than the initial/minimum duration, as well as the related resource availability cost problem. The algorithm operates within a commercial project management software package by altering the priorities assigned to activities. The hyper-heuristic controls a set of low-level heuristics, which modify the priorities of selected activities by performing simple moves such as “replace” and “swap”. The most promising heuristics according to their efficiency are applied first, and a tabu list is used to prohibit heuristics with recently poor performance from being applied too soon. The application of the algorithm in three project cases showed that the proposed procedure is promising for handling resource optimization problems.

In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic algorithm for... more In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic algorithm for solving the resource constrained project scheduling problem (RCPSP). To the best of our knowledge, this is the first attempt to develop a PSO hyper-heuristic and apply to the classic RCPSP. The hyper-heuristic works as an upper-level algorithm that controls several low-level heuristics which operate to the solution space. The solution representation is based on random keys. Active schedules are constructed by the serial scheduling generation scheme using the priorities of the activities which are modified by the low-level heuristics of the algorithm. Also, the double justification operator, i.e. a forward–backward improvement procedure, is applied to all solutions. The proposed approach was tested on a set of standard problem instances of the well-known library PSPLIB and compared with other approaches from the literature. The promising computational results validate the effectiveness of the proposed approach.

Applied Mathematics and Computation, 2010

ABSTRACT

An effective procedure for time-cost trade off in Critical Path Method (CPM) networks when discre... more An effective procedure for time-cost trade off in Critical Path Method (CPM) networks when discrete time-cost combinations are allowed on the project activities is developed. The particular problem confronted in this study is to select a time-cost combination for each activity which minimizes the project overall cost subject to a due-date. For this inherently difficult to solve problem, the heuristic algorithm constructs a feasible solution of minimal cost by compressing and increasing the duration of critical and noncritical activities. In order to improve the time efficiency of the algorithm, a subroutine is used that recalculates the critical paths by restricting the calculations to a partial network. The procedure, coded in Visual Basic and tested on a large set of randomly generated networks, has provide fairly good solutions at a small computational effort.

Project participants, through experience, have an initial perception and predisposition towards r... more Project participants, through experience, have an initial perception and predisposition towards risk and the
types of risks they are willing and able to undertake. This is equally true for parties interested in public–private
partnership (PPP) projects. These initial positions have been registered for the major Greek PPP market
stakeholders potentially involved in a PPP arrangement through a survey covering all candidate construction
companies, interested financing institutes and a number of public sector entities to be involved in PPPs.
Findings revealed that stakeholders were, for the majority of risks identified, in agreement as to preferred risk
allocation. Risk allocation preferences for construction companies were compared with similar findings for the
UK, a mature PPP market, indicating a possible learning/maturing process based on the particular country
background. Conclusions add to other surveys carried out on the subject and should enable public sector clients
to establish a more efficient framework for risk allocation, thus reducing negotiations prior to contract award
and minimizing the risk of poor risk distribution.

Operational Research, 2004

This paper investigates the ability of Multiobjective Evolutionary Algorithms (MOEAs), namely the... more This paper investigates the ability of Multiobjective Evolutionary Algorithms (MOEAs), namely the Non-dominated Sorting Genetic Algorithm II (NSGA-II), Pareto Envelope-based Selection Algorithm (PESA) and Strength Pareto Evolutionary Algorithm 2 (SPEA2), for solving complex portfolio optimization problems. The portfolio optimization problem is a typical bi-objective optimization problem with objectives the reward that should be maximized and the risk that should be minimized. While reward is commonly measured by the portfolio’s expected return, various risk measures have been proposed that try to better reflect a portfolio’s riskiness or to simplify the problem to be solved with exact optimization techniques efficiently. However, some risk measures generate additional complexities, since they are non-convex, non-differentiable functions. In addition, constraints imposed by the practitioners introduce further difficulties since they transform the search space into a non-convex region. The results show that MOEAs, in general, are efficient and reliable strategies for this kind of problems, and their performance is independent of the risk function used.

We formulate the portfolio selection as a tri-objective optimization problem so as to find tradeo... more We formulate the portfolio selection as a tri-objective optimization problem so as to find tradeoffs
between risk, return and the number of securities in the portfolio. Furthermore, quantity and class
constraints are introduced into the model in order to limit the proportion of the portfolio invested in
assets with common characteristics and to avoid very small holdings. Since the proposed portfolio
selection model involves mixed integer decision variables and multiple objectives finding the exact
efficient frontier may be very hard. Nevertheless, finding a good approximation of the efficient surface
which provides the investor with a diverse set of portfolios capturing all possible tradeoffs between the
objectives within limited computational time is usually acceptable. We experiment with the current
state of the art evolutionary multiobjective optimization techniques, namely the Non-dominated
Sorting Genetic Algorithm II (NSGA-II), Pareto Envelope-based Selection Algorithm (PESA) and Strength
Pareto Evolutionary Algorithm 2 (SPEA2), for solving the mixed-integer multiobjective optimization
problem and provide a performance comparison among them using metrics proposed by the
community.

This paper compares the effectiveness of five state-of-the-art multiobjective evolutionary algori... more This paper compares the effectiveness of five state-of-the-art multiobjective evolutionary algorithms (MOEAs) together with a steady state evolutionary algorithm on the mean–variance cardinality constrained portfolio optimization problem (MVCCPO). The main computational challenges of the model are due to the presence of a nonlinear objective function and the discrete constraints. The MOEAs considered are the Niched Pareto genetic algorithm 2 (NPGA2), non-dominated sorting genetic algorithm II (NSGA-II), Pareto envelope-based selection algorithm (PESA), strength Pareto evolutionary algorithm 2 (SPEA2), and e-multiobjective evolutionary algorithm (e-MOEA). The computational comparison was performed using formal metrics proposed by the evolutionary multiobjective optimization community on publicly available data sets which contain up to 2196 assets.

Managerial Finance, 2010

Purpose – The purpose of this paper is to present a procedure for finding the efficient frontier,... more Purpose – The purpose of this paper is to present a procedure for finding the efficient frontier, i.e. a non-decreasing curve representing the set of Pareto-optimal or non-dominated portfolios, when the standard Markowitz' classical mean-variance model is enriched with additional constraints. Design/methodology/approach – The mean-variance portfolio optimization model is extended to include integer constraints that limit a portfolio to have

International Journal of Financial Markets and Derivatives, 2011

Regarding the inability to fulfill regional landfill demands, the inefficiency of municipal solid... more Regarding the inability to fulfill regional landfill demands, the inefficiency of municipal solid waste management systems due to shortages of suitable and efficient infrastructures remains a crucial social issue. In addition, the fact that there are numerous environmental, social, and design factors that need to be taken into account by decision makers (DMs) raises serious concerns regarding the task of identifying appropriate sites for municipal solid waste landfills. For this reason, the use of multicriteria spatial decision support systems, the synergic combination of geographic information system (GIS) and multicriteria decision analysis (MCDA) methods, is proposed, taking into consideration the spatial nature of the problem and the need to incorporate conflicting objectives and DM preferences. The paper at hand proposes a framework that enables the implementation of the measuring attractiveness by a categorical based evaluation technique (MACBETH) method in GIS-based raster-driven suitability analysis. MACBETH is a well-established MCDA method for the evaluation of alternative actions/scenarios based on qualitative judgments regarding their attractiveness to a DM. A real-world case study concerning the placement of a landfill in the region of Thrace, northeastern Greece, is discussed in detail. The computational part of the MACBETH method is supported by the M-MACBETH decision support system. The proposed framework consists of an attempt that allows MACBETH implementation in GIS-based raster-driven suitability analysis. In addition, a comparative analysis with other well-known methods was conducted showing that the proposed framework produces sufficient results.

The identification of sites for locating new natural systems for wastewater treatment (NSWT), suc... more The identification of sites for locating new natural systems for wastewater treatment (NSWT), such as stabilization ponds and constructed wetlands, should combine multiple crucial factors (environmental, design, social and economic), and thus the implementation of multicriteria decision-making (MCDM) methods is required. In addition, the spatial nature of the site selection process necessitates the use of geographic information systems (GISs) because they are unanimously recognized as the most appropriate tool capable of supporting sophisticated spatial decision making. The resulting multicriteria spatial decision support systems (MC-SDSSs) provide a consistent framework for dealing with conflicting objectives while integrating the decision makers' (DMs') preferences in spatially related patterns/problems. A map-based, interactive UTAII implementation is presented, which provides a link between a well-understood decision support method and exploratory geographic visualization. Spatial UTA (S-UTA) is applied in a real case study concerning the ranking of candidate sites for implementing natural systems for wastewater treatment in the Evros–Rodopi prefectures of northeastern Greece. Finally, the obtained results are compared with those derived using other MCDM approaches to evaluate the performance of S-UTA in GIS-based land use suitability analyses.
Publication Date: May 3, 2013
Publication Name: Journal of Environmental Management

When decentralized strategies are considered for managing wastewater, natural systems for wastewa... more When decentralized strategies are considered for managing wastewater, natural systems for wastewater treatment (NSWT) (constructed wetlands) seem to be strongly preferred in comparison with the conventional activated sludge wastewater treatment systems. However, because of their high land requirements, land-use suitability analysis should be conducted to specify adequate areas for their accommodation. Multicriteria spatial decision support systems have emerged as the technology that takes into account both decision criteria and constraints in complex land-use planning problems. This study presents a multiattribute decision analysis approach called the spatial fuzzy Analytic Hierarchy Process (SFAHP) to support raster-based land-use suitability studies for the implementation of NSWT. The SFAHP enables decision makers to circumvent vagueness when they perform evaluations using linguistic variables. Its application in a region of Northeastern Greece using a two-level criteria hierarchical model demonstrates its potential use for suitability analyses.

Three alternative irrigation projects for the East Macedonia-Thrace Region, Greece, are considere... more Three alternative irrigation projects for the East Macedonia-Thrace Region, Greece, are considered. Given
the presence of valuable natural ecosystems in the area, environmental considerations are of great importance.
In order to evaluate the projects, a fuzzy multicriteria benefit–cost approach is proposed. The
overall goal is the rational management of water resources, and the projects appraisal is based on economic,
social, and environmental criteria. Alternative scenarios on the availability of water resources are
also incorporated in the decision model. The decision problem is formulated as two hierarchies, and the
projects are ranked according to the benefit–cost ratio of their global priorities. The proposed method
is proved to be, on the one hand, very suitable when both costs and benefits cannot be easily expressed
into monetary terms as the traditional benefit–cost analysis requires; and, on the other hand, a valuable
tool to cope with vague judgments.

Operational Research, 2010

Renowned for their ability to deal with spatial problems, commercial GIS software packages can pl... more Renowned for their ability to deal with spatial problems, commercial GIS software packages can play crucial role in spatial decision making processes, provided that they have tools that allow both private and public organizations to manage and analyze spatial referenced data. In particular, land-use suitability analysis applications are valuable, where the use of conflicting objectives and decision maker’s (DMs) preferences

Statistical analysis can be an important tool to identify and classify different sources of groun... more Statistical analysis can be an important tool to identify and classify different sources of groundwater salinisation. This paper refers to the application of Stepwise Discriminant Analysis (SDA) as an effective technique for the identification of major constituent ratios which can be used for efficiently identifying various salinity sources. The effectiveness of the SDA method was tested on five groups of groundwater samples known for their salinisation. Three were taken from the brackish groundwater of the Nestos River delta, from the geothermal field of Nea Kessani and the brackish groundwater of the western coastal area of Rhodope, in Greece. The remaining two groups were taken from bibliographic sources and they refer to the degraded groundwater of the Wittmund area in coastal NW Germany as well as from the underground brines of Sichuan Basin in China. The method of SDA has demonstrated its effectiveness of classifying different groundwater groups, and its usefull contribution to the groundwater contamination. In this way, possible expensive field investigations and analyses of chemical parameters can be eliminate.

In last decades, the theory of resources had been established as an important part of discussion ... more In last decades, the theory of resources had been established as an important part of discussion on the competitive operations of the firms. Its contribution for the strategic approach of creation of firms competitive advantage won recognition. However, the theory of resources was not able to put forward clear and applicable tools, and consequently, useful in formulating the firms strategy. Thus, a central question has been leaved unanswered: Finally, which are those from the resources that contribute in the configuration of the strategy and the competitive ability of the firms? In this paper it is not proposed an additional variant in the already existing views of the theory of resources; but based on these approaches, we try to determine the critical factors in the firm, that transform individual resources of tactical importance in strategic advantage in order to sustain the firms competitive ability and obtain their viability. This process occurs within a technology-people structure that composes what we name “technology-production base” of the firms.

Although each organization has some learning capabilities, a learning organization is not a spont... more Although each organization has some learning capabilities, a learning organization is not a spontaneous construction but a result of the management purposeful action. After a discussion of learning in a systemic perspective, this paper focuses on the characteristics of the learning organization, the factors that block or facilitate learning and some strategies for improving learning capabilities. Some remarks about the relationships between learning as a prerequisite of the technological and process innovation are also made.

This paper aims to translate the strategy of a Greek manufacturing company into objectives and me... more This paper aims to translate the strategy of a Greek manufacturing company into objectives and measures that can be clearly communicated to all units and employees. For this purpose two basic strategic tools are implemented, the Balanced Scorecard (BSC) and the strategy map. Based on the statements about mission, vision, and values of the company, and the strategic analysis, we formulate the strategy on four axes. The company’s strategy map is constructed using the four axes as strategic themes, and the four traditional perspectives of the BSC. Twenty eight objectives and thirty six measures are used, and nine departments are engaged to monitor the performance of objectives in order the company to achieve the determined targets. Finally, ten strategic initiatives are proposed that company must carry out to achieve the targeted performance of strategic objectives and measures.

Εισαγωγή του μεταφραστή Πρόλογος στην τρίτη έκδοση Πρόλογος στη δεύτερη έκδοση 1 Η κατανόηση του ... more Εισαγωγή του μεταφραστή Πρόλογος στην τρίτη έκδοση Πρόλογος στη δεύτερη έκδοση 1 Η κατανόηση του φυσικού και του τεχνητού κόσμου 2 Η οικονομική ορθολογικότητα Οι προσαρμοστικές επινοήσεις 3 Η ψυχολογία της σκέψης Ενσωμάτωση των επινοήσεων στη φύση 4 Ενθύμηση και μάθηση Η μνήμη ως περιβάλλον της σκέψης 5 Η επιστήμη του σχεδιασμού Η δημιουργία του τεχνητού 6 Ο κοινωνικός προγραμματισμός Ο σχεδιασμός του εξελισσόμενου τεχνήματος 7 Εναλλακτικές απόψεις για την πολυπλοκότητα 8 Η αρχιτεκτονική της πολυπλοκότητας Ιεραρχικά συστήματα Πίνακας αντιστοιχίας όρων Ευρετήριο ονομάτων

Journal of Water Resources Planning and Management, May 13, 2011

When decentralized strategies are considered for managing wastewater, natural systems for wastewa... more When decentralized strategies are considered for managing wastewater, natural systems for wastewater treatment (NSWT) (constructed wetlands) seem to be strongly preferred in comparison with the conventional activated sludge wastewater treatment systems. However, because of their high land requirements, land-use suitability analysis should be conducted to specify adequate areas for their accommodation. Multicriteria spatial decision support systems have emerged as the technology that takes into account both decision criteria and constraints in complex land-use planning problems. This study presents a multiattribute decision analysis approach called the spatial fuzzy Analytic Hierarchy Process (SFAHP) to support raster-based land-use suitability studies for the implementation of NSWT. The SFAHP enables decision makers to circumvent vagueness when they perform evaluations using linguistic variables. Its application in a region of Northeastern Greece using a two-level criteria hierarchical model demonstrates its potential use for suitability analyses.