Influence of Portfolio Management in Decision-Making

Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem has been addressed to enable on-time completion of customer orders in a lean manufacturing environment. The problem is optimizing the partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components. Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid excess final product inventory. The first model is a non-linear integer programming model whereas the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times compared to the other two models. It has also been showed that the alternative model is able to solve moderate sized real-world problems. Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature owing to the inclusion of new circumstances that are present in real-world applications. Those are: customer orders consisting of multi-products made of multi-parts, processing of all parts of the same product from different orders in the same batch, and delivering the orders only when all related products are completed. This research also contributes to the literature of batch scheduling problem by presenting new optimization models.Peer Reviewe

Multicriteria rankings of open-end investment funds and their stability

For research purposes, three multicriteria outranking methods (PROMETHEE, WSA and TOPSIS) were used to construct rankings of investment funds to assess their performance in the time period from January to July 2008. Nine indicators related to the distributions of return rates, purchase and management costs and to customers’ convenience were included in the set of criteria. The weight of each criterion was calculated on the basis of the relative volatility rate of the given criterion. In order to assess the stability of the rankings, the weight of a single criterion was changed (using each criterion in turn) and new rankings were constructed using the modified weights. The similarity of rankings built before and after these changes was assessed on the basis of the maximum difference between ranks and the Spearman correlation coefficient. The results obtained enable assessment not only of the stability of each outranking method, but the similarity of results obtained by different methods as well. All calculations were done using the SANNA software.investment funds, outranking methods, PROMETHEE method, WSA method, TOPSIS method, stability of rankings

A Decision Making System for Selecting Sustainable Technologies for Retail Buildings

CIB Publication 382: Selected papers presented at the CIB World Building Congres Construction and Society, Brisbane 5-9 May 2013 Papers from the Designated Session TG66 - Energy and the Built EnvironmentThe implementation of sustainable technologies can improve the energy and carbon efficiency of existing retail buildings. However, the selection of an appropriate sustainable technology is a complex task due to the large number of technological alternatives and decision criteria that need to be considered. Also, there exist series of uncertainties that are associated with the use of sustainable technologies, but have to be evaluated to achieve realistic and transparent results. The selection of sustainable technology is therefore most challenging. An earlier study was conducted with UK experienced practitioners including clients/developers, engineers, contractors and suppliers to identify the drivers and barriers for the use of sustainable technologies in UK retail construction. One major barrier identified from the study was the lack of a decision making tool, highlighted by both construction professionals and stakeholders in the retail industry. The large number of alternatives and potential solutions require a decision support method to be implemented. Information data on the economic variables, energy performance and impact on the environment of these systems is presently affected by vagueness and lack of knowledge. To deal with this high level of complexity and uncertainty an evaluation support approach is needed. This paper aims to develop a decision making framework to assist both retailers and construction professionals to define and evaluate the selection of sustainable technological options for delivering retail buildings. The research was carried out through a combination of a critical literature review and a survey-based study using expert opinions of retailers and contractors. The developed framework of decision criteria should provide a sustainable technology model to assist both construction professionals and stakeholders in the retail industry to systematically and effectively select the most appropriate technology. This approach should make the decision progression more transparent and facilitate sustainable development of retail buildings in achieving the carbon targets set by the UK and other governments

MULTI CRITERIA DECISION MAKING MODELS: AN OVERVIEW ON ELECTRE METHODS

In portfolio analysis, there are a few models that can be used. Therefore, the aim of this paper is to make an overview on multi criteria decision making models, in particular, on ELECTRE methods. We discuss the different versions of ELECTRE, which exist and why they exist. So, when speaking about ELECTRE methods structure, we have to consider two main procedures: construction of one or several outranking relation(s) procedure, and exploitation procedure. In the exploitation procedure, recommendations are elaborated from the results obtained in the first phase. The nature of the recommendation depends on the problematic: choosing, ranking or sorting. Each method is characterized by its construction and exploitation procedure. For choice problem, we can apply ELECTRE I, ELECTRE Iv, and ELECTRE IS; for ranking problem, we can apply ELECTRE II, ELECTRE III, ELECTRE IV and ELECTRE-SS; and for sorting problem we can apply ELECTRE TRI. Finally, some failings on ELECTRE methods assumptions are discussed, for instance, rank reversals. So, when analyzing portfolio management decision problem, the literature suggests AHP method and PROMETHEE family.CAPM; decision problem; multi criteria decision making models; ELECTRE family; ELECTRE rank reversals

Contractors Perspective on the Selection of Innovative Sustainable Technologies for Achieving Zero Carbon Retail Buildings

The use of innovative sustainable technologies (IST) has been regarded as an effective approach to enhancing energy efficiency and reducing carbon emissions of buildings. However, contractors face significant challenges in the selection of IST. The reported challenges in the literature include: lack of skills and knowledge, uncertainties, risks and the rapid development of a large number of technological alternatives and decision criteria. The selection process emerges as a multi-attribute, value-based task that includes both qualitative and quantitative factors, which are often assessed with imprecise data and human judgments. This paper aims to establish the decision criteria for the selection of IST for achieving low carbon existing retail buildings with a focus on the main contractor’s perspective. The arguments are informed by the combination of literature review and an in-depth case study with a UK leading contractor. Five broad decision criteria are identified systematically drawing on the contractor’s practice. The established criteria are weighted and ranked using the analytic hierarchy process and expert opinions; with ‘margin opportunity’ being the most important, followed by ‘repeat business’, ‘investment costs’, ‘differentiation’ and then ‘transferability’. The findings should facilitate the integration of various facets of the selection process and stimulate contractors to use IST

Operational Research in Education

Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions

Fuzzy Logic and Its Uses in Finance: A Systematic Review Exploring Its Potential to Deal with Banking Crises

The major success of fuzzy logic in the field of remote control opened the door to its application in many other fields, including finance. However, there has not been an updated and comprehensive literature review on the uses of fuzzy logic in the financial field. For that reason, this study attempts to critically examine fuzzy logic as an effective, useful method to be applied to financial research and, particularly, to the management of banking crises. The data sources were Web of Science and Scopus, followed by an assessment of the records according to pre-established criteria and an arrangement of the information in two main axes: financial markets and corporate finance. A major finding of this analysis is that fuzzy logic has not yet been used to address banking crises or as an alternative to ensure the resolvability of banks while minimizing the impact on the real economy. Therefore, we consider this article relevant for supervisory and regulatory bodies, as well as for banks and academic researchers, since it opens the door to several new research axes on banking crisis analyses using artificial intelligence techniques

Mixed Signals: Why investors may misjudge first time high technology founders

This paper seeks to explain an unexpected result of a previous quantitative study which suggested sub-optimal evaluation by investors of the human capital of first time high tech venture founders. A literature review revealed two possible reasons for this finding: biases/heuristics and signaling. Six investors across three countries (one venture capitalist and one business angel each from the US, UK and Israel) with experience in investing in early stage high technology ventures were interviewed using an identical semi-structured interview protocol. This research design is appropriate for research that seeks to reflect back unexpected findings of previous quantitative research on the subjects of research. Interviewees were first asked to state their own investment criteria, and then presented with the results of the quantitative study and asked for their views. Previous research suggesting a gap between in-use and espoused criteria, and extensive use of gut feeling in decision-making, was supported. Interviewees focused on harvest potential and de-emphasised measures of founder technology capability that predicted early survival and growth in the earlier study. The paper concludes by suggesting how investors might improve funding decisions in high tech ventures led by first-time entrepreneurs, noting the study's limitations and making recommendations for further research

Mid-term Evaluation of NGO Programmes Under EEA Grants 2009-2014

The EEA Financial Mechanism (2009-2014) have committed 160,4 million to support seventeen NGO Programmes in sixteen countries: Bulgaria, Croatia, Cyprus, the Czech Republic, Estonia, Greece, Hungary, Latvia, Lithuania, Malta, Poland, Portugal, Romania, the Slovak Republic, Slovenia and Spain. The overall objective of the EEA Grants NGO Programmes is strengthened civil society development and enhanced contribution to social justice, democracy and sustainable development in each of the beneficiary countries. As of 30 of June 2014, 957 projects in total of 53,793,561 have been supported mainly in the fields of democracy, citizen participation, human rights, social justice and empowerment, sustainable development and provision of basic welfare services. The mid-term evaluation of the NGO Programmes funded by the EEA Financial Mechanism (2009- 2014) is an independent formative evaluation. Its objective was two-fold: 1) to assess the progress and needs for improvement of the current Programmes, and 2) to inform policies for the next financial period. The main purpose of this evaluation was to provide an expert independent mid-term assessment of the contribution of the EEA Grants 2009-2014 to the NGO sectors in the beneficiary states operating NGO Programmes. The evaluation was of dual nature: (1) of a formative evaluation to identify progress and needs for improvement of the current Programmes and (2) of a forward oriented strategic review to inform policies for the next financial period

Increasing the density of available pareto optimal solutions

The set of available multi-objective optimization algorithms continues to grow. This fact can be partially attributed to their widespread use and applicability. However this increase also suggests several issues remain to be addressed satisfactorily. One such issue is the diversity and the number of solutions available to the decision maker (DM). Even for algorithms very well suited for a particular problem, it is difficult - mainly due to the computational cost - to use a population large enough to ensure the likelihood of obtaining a solution close to the DMs preferences. In this paper we present a novel methodology that produces additional Pareto optimal solutions from a Pareto optimal set obtained at the end run of any multi-objective optimization algorithm. This method, which we refer to as Pareto estimation, is tested against a set of 2 and 3-objective test problems and a 3-objective portfolio optimization problem to illustrate its’ utility for a real-world problem