Multi-criteria decision making for choosing socially responsible investment within a behavioral portfolio theory framework: a new way of investing into a crisis environment

The current economic crisis fuels the financial social responsibility after an epoch of many excesses with damaging effects. This work tackles two emerging streams in the financial literature: the behavioral portfolio theory with mental accounting and the socially responsible investment (SRI). Promoting SRI is regarded by a lot of financial experts, policymakers and researchers from the field of economic and social sciences, as one of the potential solutions in order to avoid future crises. Therefore, new models for this investment approach are necessary. We try to support the class of investors that select their investments under a mental accounting framework and also they want to achieve a certain level of SR quality in their portfolios. In order to reconcile the two choice frames, avoiding unnecessary sacrifices in financial performance, we have designed a model based on goal programming that integrates the two cornerstones of the investor. Furthermore, we propose a fuzzy inference system to determine the amount of money allocated to each mental account as well as the confidence level assigned to each mental account. This tool is based on expert knowledge modeled by fuzzy if–then rules.     

Using DEA as a tool for MCDM: some remarks

The purpose of this paper is to study proposals to use Data Envelopment Analysis (DEA) as a tool for Multiple Criteria Decision Making (MCDM). We first recall, using a simple model, the equivalence between the concept of ‘efficiency’ in DEA and that of ‘convex efficiency’ in MCDM. Examples are then used to show that various techniques that have been proposed in the DEA literature to deal with MCDM problems violate simple normative properties that are commonly accepted. We conclude with some remarks on the possible areas of interaction between DEA and MCDM.     

The effective model of a stratified solid-fluid medium as a special case of the Biot model

The Biot model is compared with the effective model of a stratified periodic elastic-fluid medium, and the parameters of the transversally isotropic Biot model that turn it into the effective model are found. In the course of this comparison, some intermediate models, which are generalizations of the effective model and particular cases of the Biot model, are considered. For all of the models, the wave fronts excited by a point source are determined. The distinguishing feature of wave fronts in the intermediate models is the occurrence of double loops on some of them. Bibliography: 15 titles. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 230, 1995, pp. 172–195. Translated by L. Molotkov     

Using a MILP model to establish a framework for an annualised hours agreement

Production flexibility is essential for industrial companies that have to deal with seasonal demand. Human resources are one of the main sources of flexibility. Annualising working hours (i.e., the possibility of irregularly distributing the total number of working hours over the course of a year) is a tool that provides flexibility to organizations; it enables a firm to adapt production capacity to fluctuations in demand. However, it can imply a worsening of the staff’s working conditions. To take the human aspect into account, the planning and scheduling of working time should comply with constraints derived from the law or from a collective bargaining agreement. Furthermore, new and more difficult working-time planning and scheduling problems are arising. This paper proposes a mixed-integer linear program model to solve the problem of planning the production and the working hours of a human team that operates in a multi-product process. Solving the model for different settings provides the essential quantitative information to negotiate the best conditions of the annualised hours system (the elements to establish the trade-off between weekly flexibility and economic or working-time reduction compensation can be obtained). The results achieved in a computational experiment were very satisfactory.     

Combination of MCDM and covering techniques in a hierarchical model for facility location: A case study

In this paper, locating some warehouses as distribution centers (DCs) in a real-world military logistics system will be investigated. There are two objectives: finding the least number of DCs and locating them in the best possible locations. The first objective implies the minimum cost of locating the facilities and the latter expresses the quality of the DCs locations, which is evaluated by studying the value of appropriate attributes affecting the quality of a location. Quality of a location depends on a number of attributes; so the value of each location is determined by using Multi Attribute Decision Making models, by considering the feasible alternatives, the related attributes and their weights according to decision maker’s (DM) point of view. Then, regarding the obtained values and the minimum number of DCs, the two objective functions are formed. Constraints imposed on these two objectives cover all centers, which must be supported by the DCs. Using Multiple Objective Decision Making techniques, the locations of DCs are determined. In the final phase, we use a simple set partitioning model to assign each supported center to only one of the located DCs.     

Linear time-periodic dynamical systems: an H2 analysis and a model reduction framework

Linear time-periodic (LTP) dynamical systems frequently appear in the modelling of phenomena related to fluid dynamics, electronic circuits and structural mechanics via linearization centred around known periodic orbits of nonlinear models. Such LTP systems can reach orders that make repeated simulation or other necessary analysis prohibitive, motivating the need for model reduction. We develop here an algorithmic framework for constructing reduced models that retains the LTP structure of the original LTP system. Our approach generalizes optimal approaches that have been established previously for linear time-invariant (LTI) model reduction problems. We employ an extension of the usual H₂ Hardy space defined for the LTI setting to time-periodic systems and within this broader framework develop an a posteriori error bound expressible in terms of related LTI systems. Optimization of this bound motivates our algorithm. We illustrate the success of our method on three numerical examples.     

The spectral decomposition of a covariance matrix for the balanced mixed analysis of variance model

We derive the spectral decomposition of a covariance matrix for the balanced mixed analysis of variance model. The derivation is based on determining the distinct eigenvalues of a covariance matrix and then obtaining a principal idempotent matrix for each distinct eigenvalue. Examples are given to illustrate the results.     

Towards an auction-driven gas supply: a simulation-based optimization framework for utilities

A platform for the study of the whole transmission problem (arrival of ships, regasification, transportation and distribution) faced by gas utilities companies is proposed. The main objective of this research is to develop a platform that includes the analysis of the new capacity auctions (and not the traditional commodity auctions) that will govern the supply chain in the near future. A simulation-optimization approach has been used to favour the more realistic abstraction of the system. The discrete-event model includes a genetic algorithm to reach the solution in a satisfactory short time, a requisite in auction markets. Design and optimization studies for the utilities are addressed using the platform, which has been validated with real data for one of the main zones in the Spanish market.     

The radar method: an effective line search for piecewise linear concave functions

The maximization of one-dimensional piecewise linear concave (OPLC) functions arises in the line search associated with the maximization of piecewise linear concave functions (e.g. Kelley cutting plane method). The OPLC line search is usually done by the next-break-point method, where one goes from break point to break point up to the optimum. If the number of break points is large this method will be computationally expensive. One can also use some classical derivative-free line search method as for example the golden section method. Such methods do not take advantage of the OPLC geometry. As an alternative, we propose an improved version of the so-called radar method, which maximizes an OPLC function by maximizing successive outer approximations. We prove superlinear and finite convergence of the radar method. Furthermore, our computational test shows that the radar method is highly effective independently from the number of break points.     

A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO

This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms for multiobjective optimization is given. A substantial number of methods has been proposed so far, and an attempt of conceptually unifying existing approaches is presented here. Based on a fine-grained decomposition and following the main issues of fitness assignment, diversity preservation and elitism, a conceptual model is proposed and is validated by regarding a number of state-of-the-art algorithms as simple variants of the same structure. This model is then incorporated into the ParadisEO-MOEO software framework. This framework has proven its validity and high flexibility by enabling the resolution of many academic, real-world and hard multiobjective optimization problems.     

Analysis of tumor as an inverse problem provides a novel theoretical framework for understanding tumor biology and therapy

We use a novel “inverse problem” technique to construct a basic mathematical model of the interacting populations at the tumor-host interface. This approach assumes that invasive cancer is a solution to the set of state equations that govern the interactions of transformed and normal cells. By considering the invading tumor edge as a traveling wave, the general form of the state equations can be inferred. The stability of this traveling wave solution imposes constraints on key biological quantities which appear as parameters in the model equations. Based on these constraints, we demonstrate the limitations of traditional therapeutic strategies in clinical oncology that focus solely on killing tumor cells or reducing their rate of proliferation. The results provide insights into fundamental mechanisms that may prevent these approaches from successfully eradicating most common cancers despite several decades of research. Alternative therapies directed at modifying the key parameters in the state equations to destabilize the propagating solution are proposed.     

The heterogeneous multiscale method as a framework for coupling the finite element method and molecular dynamics

Hierarchical two-scale methods are computationally very powerful as there is no direct coupling between the macro- and microscale. Such schemes develop first a microscale model under macroscopic constraints, then the macroscopic constitutive laws are found by averaging over the microscale. The heterogeneous multiscale method (HMM) is a general top-down approach for the design of multiscale algorithms. While this method is mainly used for concurrent coupling schemes in the literature, the proposed methodology also applies to a hierarchical coupling. This contribution discusses a hierarchical two-scale setting based on the heterogeneous multi-scale method for quasi-static problems: the macroscale is treated by continuum mechanics and the finite element method and the microscale is treated by statistical mechanics and molecular dynamics. Our investigation focuses on an optimised coupling of solvers on the macro- and microscale which yields a significant decrease in computational time with no associated loss in accuracy. In particular, the number of time steps used for the molecular dynamics simulation is adjusted at each iteration of the macroscopic solver. A numerical example demonstrates the performance of the model. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Preconditions for constructing a biomechanical model of the heart as an integral musculovascular organ

Conclusion Relative to its major function, pumping, the heart should be considered as an integral musculovascular organ. It is precisely this integration in the structural and functional sense which permits the heart not only to perform its pump function as a converter of chemical energy supplied by the blood into mechanical flow energy but also to combine the supply and conversion of energy into a single cycle, produce the hydrodynamics of cardiac output in definite fashion, and introduce a correction into the filling phase according to current arterial pressure as the most dynamic index of systemic hemodynamics. The breakdown of the structure of the cardiac pump into elements differing in their functional significance permits us to delineate at least three channels for the utilization of energy supplied to the heart and consumed in the major pumping function: the mechanical work performed by the lower part of the cardiac muscle that is displaced into the ventricular space, the energy consumed on maintaining the systolic pressure of the myocardial fibers which form the relatively immobile upper and side walls of the heart, and the energy consumed on maintaining the high tone of the muscular walls of the coronary arteries and arterioles which form the hydraulic frame of the heart.A representation of the heart which includes muscular and vascular components, in our view, is the basic prerequisite for the development of mathematical models for the cardiac pump based on energy balance equations and suitable for solving the problems posed by clinical medicine in regard to auxiliary blood circulation.Translated from Mekhanika Kompozitnykh Materialov, No. 4, pp. 699–702, July–August, 1980.     

The perspective of a bank in granting credits: an optimization model

In this work, a model for legal financiers’ strategies is presented, taking into account that the aim of a bank is to minimize the default probability of the funded company, constrained with reaching a certain profit level. To obtain our purpose, a stochastic dynamics optimization model is constructed and solved in closed form and a Monte Carlo simulation involving empirical data is also implemented. The financial strategies are thus obtained.     

On the boundary-value problem for a mixed-type equation: Asymptotic analysis and an effective numerical algorithm

A singularly perturbed boundary-value problem for an equation of mixed ellipticparabolic type is considered. The first part of this work is devoted to an asymptotic study of the solution to the problem. Modification of the boundary function method for mixed-type equations with small parameters at the highest derivatives is used. The second part is devoted to creating a numerical method that considers the structure of the solution for small parameter values. The idea of an approximate factorization of an elliptic operator into the product of two parabolic operators is employed. An effective numerical algorithm based on an asymptotic representation of the solution is developed.     

A multi-criteria framework as a decision support system for urban growth management applications: Central city redevelopment

The paper introduces a decision support system based on a multi-criteria framework that integrates several socio-economic, physical planning and urban design processes recently used in the U.S. for growth management of central city redevelopment. It formalizes and operationalizes the concept of the ‘critical coalition’, i.e. user groups representative of the community's interests who share common perceived values, objectives and problems within an urban setting. This critical coalition provides the decision model with the socio-economic qualitative input to establish representative priorities and importance weights, and to provide the political base for the implementation of policy actions. The framework is applied to establish locational suitability of development or redevelopment actions within a central city. This application is illustrated with examples from a pilot study to establish the suitability of residential infill within the central business district of the City of Columbus, Ohio.     

A linear production-exchange model: Polyhedral complexes and a criterion for an equilibrium

Under study is an economic model of exchange whose participants include consumers as well as companies producing commodities. The production capabilities of the companies are constrained by the expenses of a certain single resource. We scrutinize the version of the model with fixed budgets of the participants, show that some equilibrium exists, and describe an original approach of polyhedral complementarity which enables us to obtain a criterion for an equilibrium state. Thus, we can propose a finite algorithm for finding an equilibrium.     

The Sherrington–Kirkpatrick model: a challenge for mathematicians

Summary. The Sherrington–Kirkpatrick (SK) model for spin glasses is deceptively simple to state. Yet its rigorous study represents a considerable challenge. We report here some modest progresses (obtained through elementary methods). Even in the supposedly simple high temperature region, a number of basic questions remain unsolved. Received: 7 December 1995 / In revised form: 6 March 1997