Şule Önsel

Efficient shift scheduling in the retail sector through two-stage optimization

Efficient workforce scheduling has an important impact on store profit and customer service. Standard scheduling problems do not recognize the effect of staff availability on customer sales, however, even though the latter is an important factor in the retail sector. In this paper a two-stage model is proposed for this purpose. In the first stage a sales response model is used to specify hourly staff requirements. The output of the sales response model is then used as the input of a mixed integer optimization model, which finds an optimum assignment of the staff to daily shifts. Simulations are used to validate the sales response function, and to revise the model for more accurate results. In the simulations, customer arrivals and sales response error values are generated using appropriate distribution functions. As a case study the proposed model is applied to a Turkish retailer in the apparel sector.

A methodology for the strategic design of reverse logistics networks and its application in the Turkish white goods industry

In this study, a multi-objective model for the reverse logistics network design (RLND) problem and a novel methodology are proposed. The proposed methodology is comprised of two stages: the centralised return centre (CRC) evaluation stage and the reverse logistics network design (RLND) stage. In the first stage an integrated ANP and fuzzy-TOPSIS methodology is utilised. In the second stage, using the CRC weights obtained in the first stage, the RLND model is solved via genetic algorithms (GAs). The proposed methodology is applied to a case from the Turkish white goods industry. The results are discussed and analysed.

Optimizing Fire Station Locations for the Istanbul Metropolitan Municipality

The Istanbul Metropolitan Municipality IMM seeks to determine locations for additional fire stations to build in Istanbul; its objective is to make residences and historic sites reachable by emergency vehicles within five minutes of a fire station’s receipt of a service request. In this paper, we discuss our development of a mathematical model to aid IMM in determining these locations by using data retrieved from its fire incident records. We use a geographic information system to implement the model on Istanbul’s road network, and solve two location models—set-covering and maximal-covering—as what-if scenarios. We discuss 10 scenarios, including the situation that existed when we initiated the project and the scenario that IMM implemented. The scenario implemented increases the city’s fire station coverage from 58.6 percent to 85.9 percent, based on a five-minute response time, with an implementation plan that spans three years.

A decision support methodology to enhance the competitiveness of the Turkish automotive industry

Three levels of competitiveness affect the success of business enterprises in a globally competitive environment: the competitiveness of the company, the competitiveness of the industry in which the company operates and the competitiveness of the country where the business is located. This study analyses the competitiveness of the automotive industry in association with the national competitiveness perspective using a methodology based on Bayesian Causal Networks. First, we structure the competitiveness problem of the automotive industry through a synthesis of expert knowledge in the light of the World Economic Forum’s competitiveness indicators. Second, we model the relationships among the variables identified in the problem structuring stage and analyse these relationships using a Bayesian Causal Network. Third, we develop policy suggestions under various scenarios to enhance the national competitive advantages of the automotive industry. We present an analysis of the Turkish automotive industry as a case study. It is possible to generalise the policy suggestions developed for the case of Turkish automotive industry to the automotive industries in other developing countries where country and industry competitiveness levels are similar to those of Turkey.

Critical Success Factors for the Iron and Steel Industry in Turkey: A Fuzzy DEMATEL Approach

The attempt to improve the efficiency and competitiveness of an industrial sector is aided by the determination of critical success factors (CSFs) which focus efforts in those areas that really affect the whole industry, thereby conserving limited resources. In this paper, a three-stage methodology is proposed to find CSFs for an industrial sector. The methodology specifies the interrelations between factors that shape the global competitiveness of a country as a whole and those that shape the competitiveness of the particular industry in question. It integrates a Web-based survey, a Delphi-type workshop, and a fuzzy decision making trial and evaluation laboratory model to highlight those CSFs upon which policymakers should especially concentrate in order to increase the competitiveness of a given industry. This methodology is then applied to a case study, identifying the CSFs of the iron and steel industry in Turkey. The results show that the burden of custom procedures, total tax rate, scope and impact of taxation, and solidity of banks are the CSFs for the competitiveness of the Turkish iron and steel industry.

Cumulative belief degrees approach for analyzing the competitiveness of the automotive industry

As traditional competition becomes global, businesses fail to take, on their own, the measures that are required to become more competitive. Hence, in a globally competitive environment, national improvement and competitiveness have also become vital. Businesses must utilize and be supported by the international competitiveness of their nations. This study aims to analyze the competitiveness of the automotive industry from a national competitiveness perspective, using a three-stage methodology. For this purpose, a novel cumulative belief degrees (CBD) approach is introduced, to quantify the causal relations among the variables in the system. This methodology is illustrated by the analysis of the Turkish automotive industry for developing suggestions to assist policymakers in their decisions to improve the competitiveness of the industry. Although the findings are country specific, the methodology is applicable to a wider range of industries in developed and developing countries.

Operations research methodologies, edited by A. Ravi Ravindran

‘‘Operations research methodologies’’ edited by A. Ravi Ravindran covers a wide range of OR models and methods. The book begins with a brief OR history by the editor of the book. The main text contains 14 chapters, all with references sections at the end, and a thorough index is also provided. Since there is a wide range of literature concerning OR methods, this book has to be regarded as a quick reference and a general summary about OR techniques. That is why it is appropriate mostly for OR practitioners from business, industry and government. The first chapter focuses on Linear Programming (LP), through classic examples such as diet, blending and multi-period production planning problems, as well as the methods used to solve these LP models. Transformation of variables to deal with piecewise linear objective functions and multi objective LP models are also studied in this chapter. Chapter 2 consists of nonlinear programming (NLP) including both constrained and unconstrained optimisation modes. A summary of the basic algorithms of NLP are presented in this context. Several search methodologies and optimisation methods along with their related algorithms are introduced. Integer programming (IP) is covered in Chapter 3. Basic IP models such as capital budgeting and fixed charge problems in addition to branch and bound method & cutting plane algorithms have been studied in this chapter. Examples using both of the algorithms are also given. In Chapter 4, one of the most important and widely used mathematical programming models, namely network optimisation problems are studied in conjunction with sample problems. Minimum cost flow, multi-commodity flow and minimum spanning tree problems are analysed as the basic models of network optimisation. Since decision problems generally exhibit multiple and conflicting criteria for evaluating alternatives, Chapter 5 is dedicated to Multi Criteria Decision Making (MCDM). After defining some basic concepts that appear in the literature, most known/ used methods for both finite and infinite alternatives namely AHP, Promethee and Electre as well as goal programming are introduced. Although one cannot learn the details of the above mentioned methodologies, he/she can have an idea about them with these introductory explanations. MCDM software information is also given at the end of the chapter. The information needed in decision making process varies greatly. Consequently there occur some situations that have uncertainty or risk in their nature. Although decision making under risk or uncertainty is a hard task to accomplish there are numerous ways to deal with such problems, some of which are analysed in Chapter 6. The chapter has a resource section at the end which is a good reference for the readers. Another important programming technique in OR is dynamic programming working with a sequence of interrelated sub problems arranged in stages so that each problem is more tractable than the original problem. The details of the dynamic programming methodology are given in Chapter 7. Both deterministic and stochastic dynamic