Hybrid resolution approaches for dynamic assignment problem of reusable containers

In this study, we are interested in the reusing activities of reverse logistics. We focus on the dynamic assignment of reusable containers problem (e.g. gas bottles, beverages, pallets, maritime containers, etc.). The objective is to minimize the collect, reloading, storage and redistribution operations costs over a fixed planning horizon taking into account the greenhouse gas emissions. We present a new generic Mixed Integer Programming (MIP) model for the problem. The proposed model was solved using the IBM ILOG CPLEX optimization software; this method yield exact solutions, but it is very time consuming. So we adapted two hybrid approaches using a genetic algorithm to solve the problem at a reduced time (The second hybrid approach is enhanced with a local search procedure based on the Variable Neighborhood Search VNS). The numerical results show that both developed hybrid approaches generate high-quality solutions in a moderate computational time, especially the second hybrid method

Fixed-to-mobile substitution in the US, EU, and China: Forecasting technology diffusion using the Lotka-Volterra Competition model

Objectives The first purpose of this thesis is to test the performance of the Lotka – Volterra Competition model in forecasting demand for technologies. Secondly, the paper aims to determine the interrelationship between the markets and their expected behaviors based on population theories. Thirdly, it attempts to gauge the similarities and differences of market behaviors in the most developed economies based on GDPpc as of October 2018. Summary Total annual subscription for each market was used to perform in-sample forecasts. Parameterization was obtained using the Gauss-Newton non-linear least squares method with the Marquardt algorithm. Then, the stable equilibria were shown in the interactive outcome graphs, which indicate that the theoretical suggestions are well-supported by historical market patterns. Conclusions The results indicate high fitting performance (R-squares>0.98) with estimated data close to that of actual observations. Despite data complications, the model has a good degree of accuracy. The competitive relationships for the US, the EU, and China are suggested to be amensalism, amensalism, and pure competition, respectively. The equilibrium analyses show that in all scenarios, the mobile cellular market dominates the fixed-line phone market. Over time, mobile phones will substitute fixed – line phones and obtain maximum growth

When costs from being a constraint become a driver for concept generation

Managing innovation requires solving issues related to the internal development and engineering processes of a company (supply side), in addition to facing the market and competition (demand side). In this context, the product development process is crucial, as different tradeoffs and issues that require managerial attention tend to arise. The main challenges result in managers requiring practical support tools that can help them in planning and controlling the process, and of designers requiring them for supporting their design decisions. Hence, the thesis aims to focus on product costs to understand its influence on design decisions as well as on the overall management of the product development process. The core part of the thesis is based on the models and methods developed for enhancing cost analysis at the beginning of the product development process. This investigation aims to determine the importance of cost estimation in improving the overall performance of a newly designed product. The focus on post-sales and, more generally, on the customer, has become so relevant that manufacturers have to take into account not only the most obvious aspects about the product and related services, but even consider the associated implications for customers during product use. However, implementing a product life cycle perspective is still a challenging process for companies. From a methodological perspective, the reasons include uncertainty regarding the available approaches and ambiguity about their application. In terms of implementation, the main challenge is the long-term cost management, when one considers uncertainty in process duration, data collection, and other supply chain issues. In fact, helping designers and managers efficiently understand the strategic and operational consequences of a cost analysis implementation is still a problem, although advanced methodologies for more in-depth and timely analyses are available. And this is even more if one considers that product lifecycle represents a critical area of investment, particularly in light of the new challenges and opportunities provided by big data analysis in the Industry 4.0 contexts. This dissertation addresses these aspects and provides a methodological approach to assess a rigorous implementation of life-cycle cost while discussing the evidence derived from its operational and strategic impacts. The novelty lies in the way the data and information are collected, dynamically moving the focus of the investigation with regard to the data aggregation level and the product structure. The way the techniques have been combined represents a further aspect of novelty. In fact, the introduced approach contributes to a new trend in the Product Cost Estimation (PCE) literature, which suggests the integration of different techniques for product life-cycle cost analysis. The findings obtained at the end of the process can be employed to assess the impact of platform design strategy and variety proliferations on the total life-cycle costs. By evaluating the possible mix of options, and hence offering the optimal product configuration, a more conscious way for planning the product portfolio has been provided. In this sense, a detailed operational analysis (as the cost estimation) is used to inform and drive the strategic planning of the portfolio. Finally, the thesis discusses the future opportunities and challenges for product cost analysis, assessing how digitalisation of manufacturing operations may affect the data gathering and analysis process. In this new environment, the opportunity for a more informed, cost-driven decision-making will multiply, leading to varied opportunities in this research field

Combining time series analysis and multi criteria decision making techniques for forecasting financial performance of banks in Turkey

Forecasting plays a major role in financial planning and it is an essential analytical tool in banks’ strategies. In recent years, researchers are developing new techniques for estimation. Financial performance evaluation of banks is a kind of multi-criteria decision making (MCDM) problem which has developed rapidly. It is very important for a firm to monitor a wide range of performance indicators in order to ensure that appropriate and timely decisions and plans can be made. Suitable performance measures can ensure that managers adopt a long-term perspective and allocate the company’s resources to the most effective activities. The aim of this study is to evaluate the financial performance model of Turkish Banks during 2012-2015 using forecasting (based on 2002-2011 data) methods and multi criteria decision techniques. As forecasting analysis tools, classical time series methods such as moving averages, exponential smoothing, Brown's single parameter linear exponential smoothing, Brown’s second-order exponential smoothing, Holt's two parameter linear exponential smoothing and decomposition methods applied to financial ratios data. After forecasting techniques Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodologies are used for the outranking of banks. This model is applied to a case study for the financial performance evaluation of 3 state banks (Ziraat Bank, Halk Bank and Vakıflar Bank); 9 private banks (Akbank; Anadolubank; Sekerbank; Tekstil Bank; Turkish Bank; Turk Ekonomi Bank; Garanti Bank; Is Bank and Yapı Kredi Bank) and 5 foreign banks (Denizbank; Eurobank Tekfen; Finans Bank; HSBC Bank and ING Bank) in Turkey. Financial performances of a bank is divided into ten groups including Capital Ratios, Balance Sheet Ratios, Assets Quality, Liquidity, Profitability, Income-Expenditure Structure, Share in Sector, Share in Group, Branch Ratios and Activity Ratios as described by the Banks Association of Turkeypeer-reviewe