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https://hdl.handle.net/20.500.12395/41001

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Nurse scheduling with opposition-based parallel harmony search algorithm
(WALTER DE GRUYTER GMBH, 2019) Cetin Yagmur, Ece.; Sarucan, Ahmet.
One of the advances made in the management of human resources for the effective implementation of service delivery is the creation of personnel schedules. In this context, especially in terms of the majority of health-care systems, creating nurse schedules comes to the fore. Nurse scheduling problem (NSP) is a complex optimization problem that allows for the preparation of an appropriate schedule for nurses and, in doing so, considers the system constraints such as legal regulations, nurses' preferences, and hospital policies and requirements. There are many studies in the literature that use exact solution algorithms, heuristics, and meta-heuristics approaches. Especially in large-scale problems, for which deterministic methods may require too much time and cost to reach a solution, heuristics and meta-heuristic approaches come to the fore instead of exact methods. In the first phase of the study, harmony search algorithm (HSA), which has shown progress recently and can be adapted to many problems is applied for a dataset in the literature, and the algorithm's performance is evaluated by comparing the results with other heuristics which is applied to the same dataset. As a result of the evaluation, the performance of the classical HSA is inadequate when compared to other heuristics. In the second phase of our study, by considering new approaches proposed by the literature for HSA, the effects on the algorithm's performance of these approaches are investigated and we tried to improve the performance of the algorithm. With the results, it has been determined that the improved algorithm, which is called opposition-based parallel HSA, can be used effectively for NSPs.
On the Recursive Sequence xn+1=xn?(k+1)1+xnxn?1…xn?k
(Springer New York LLC, 2018) Şimşek, Dağıstan; Abdullayev, Fahreddin G.
A solution of the following difference equation is investigated: xn+1 = xn?(k+1) 1 +xnxn?1...xn?k , n = 0,1,2,... where x?(k+1),x?k,...,x?1,x0 ? (0,?) and k = 0,1,2,... .
On the Recursive Sequence xn+1 = xn?(4k+3) 1+ 2 ? t=0
(Springer New York LLC, 2017) Şimşek, Dağıstan; Abdullayev, Fahreddin G.
The solution of the difference equation (Formula presented.),..., where x?(4k+3), x?(4k+2),..., x?1, x0 ? (0, ?) and k = 0, 1,..., is studied.
Eşzamanlı dağıtımlı ve toplamalı araç rotalama problemlerinin çözümü için bakteriyel besin arama optimizasyonu tabanlı bir algoritma
(2013) Hezer, Seda; Kara, Yakup
Eşzamanlı Dağıtımlı ve Toplamalı Araç Rotalama Probleminde (EDT_ARP), her müşteri dağıtım talebi ile birlikte aynı zamanda toplama talebinde bulunmaktadır ve müşterilere eşzamanlı olarak hizmet verilmektedir. EDT_ARP çözümü oldukça zor kombinatoryal optimizasyon problemidir. Bu nedenle son yıllarda yapılan çalışmalarda metasezgisel metotlar üzerinde odaklanıldığı gözlemlenmiştir. Bu çalışmada oldukça yeni bir metasezgisel algoritma olan Bakteriyel Besin Arama Optimizasyonu Algoritması (BBAOA) tabanlı bir sezgisel çözüm yaklaşımı geliştirilmiş ve performansı değerlendirilmiştir. Çalışma kapsamında EDT_ARP katedilen toplam mesafe minimize edilerek çözülmüş ve sonuçlar literatürde bilinen ekleme tabanlı sezgisel bir algoritma ile karşılaştırılmıştır. Önerilen BBAOA ile göz önünde bulundurulan, toplam 40 test probleminden 24ünde karşılaştırma yapılan algoritmaya göre daha iyi sonuçlara ulaşılmıştır.
Açık Atölye Ti?pi? Çi?zelgeleme Problemleri?ni?n Paralel Kanguru Algori?tması ile Çözümü
(2012) Baysal, M. Emin; Durmaz, Taha; Sarucan, Ahmet; Engin, Orhan
The open shop scheduling problem is essentially a sort of scheduling problem that each job has only one operation to be processed on each machine and the processing order is not significant. It has been mainly encountered in a facility that is manufacturing similar types of products groups. In this study, open shop scheduling problems were solved in order to minimize the total make-span with Parallel Kangaroo algorithm which runs by the random jumping method. Parallel Kangaroo Algorithm is a meta-heuristic algorithm which continuously tries to reach the better solutions. The open shop scheduling instances for the benchmarking in the literature were solved with a Kangaroo Algorithm in which the wild and the tame kangaroo operators are operated in a parallel manner. The yielded results were compared with the best results in the literature. It has been found the performance of the Parallel Kangaroo Algorithm for solving the open shop scheduling problems was efficient.
Çok Kullanımlı ve Zaman Pencereli? Araç Rotalama Problemi? İçi?n Bi?r Matemati?ksel Model
(2012) Koç, Çağrı; Karaoğlan, İsmail
In this paper, the vehicle routing problem with time windows and multiple use of vehicles (VRP-TW-MUV) which is the generalized version of the classic vehicle routing problem, is considered. Unlike the classic Vehicle Routing Problem, vehicles are allowed to use more than one route in the VRP-TW-MUV. The VRP-TW-MUV is encountered usually in the distribution systems in which the product's shelf-life is short or duration of the distribution is short. Although, the VRP-TW-MUV is often encountered in practice, there are very few studies in literature. In this study, a mathematical model proposed for the VRP-TW-MUV. The proposed mathematical model is compared in terms of time to reach the best solution on the test problems of various sizes derived from the literature.
Açık Atölye Ti?pi? Çi?zelgeleme Problemleri?ni?n Paralel Kanguru Algori?tması ile Çözümü
(GAZI UNIV, FAC ENGINEERING ARCHITECTURE, 2012) Baysal, M. Emin; Durmaz, Taha; Sarucan, Ahmet; Engin, Orhan
The open shop scheduling problem is essentially a sort of scheduling problem that each job has only one operation to be processed on each machine and the processing order is not significant. It has been mainly encountered in a facility that is manufacturing similar types of products groups. In this study, open shop scheduling problems were solved in order to minimize the total make-span with Parallel Kangaroo algorithm which runs by the random jumping method. Parallel Kangaroo Algorithm is a meta-heuristic algorithm which continuously tries to reach the better solutions. The open shop scheduling instances for the benchmarking in the literature were solved with a Kangaroo Algorithm in which the wild and the tame kangaroo operators are operated in a parallel manner. The yielded results were compared with the best results in the literature. It has been found the performance of the Parallel Kangaroo Algorithm for solving the open shop scheduling problems was efficient.
Supply Chain Optimisation with Assembly Line Balancing
(TAYLOR & FRANCIS LTD, 2012) Paksoy, Turan; Özceylan, Eren; Gökçen, Hadi
Supply chain management operates at three levels, strategic, tactical and operational. While the strategic approach generally pertains to the optimisation of network resources such as designing networks, location and determination of the number of facilities, etc., tactical decisions deal with the mid-term, including production levels at all plants, assembly policy, inventory levels and lot sizes, and operational decisions are related to how to make the tactical decisions happen in the short term, such as production planning and scheduling. This paper mainly discusses and explores how to realise the optimisation of strategic and tactical decisions together in the supply chain. Thus, a supply chain network (SCN) design problem is considered as a strategic decision and the assembly line balancing problem is handled as a tactical decision. The aim of this study is to optimise and design the SCN, including manufacturers, assemblers and customers, that minimises the transportation costs for determined periods while balancing the assembly lines in assemblers, which minimises the total fixed costs of stations, simultaneously. A nonlinear mixed-integer model is developed to minimise the total costs and the number of assembly stations while minimising the total fixed costs. For illustrative purposes, a numerical example is given, the results and the scenarios that are obtained under various conditions are discussed, and a sensitivity analysis is performed based on performance measures of the system, such as total cost, number of stations, cycle times and distribution amounts.
Organizational Strategy Development in Distribution Channel Management Using Fuzzy AHP and Hierarchical Fuzzy Topsis
(PERGAMON-ELSEVIER SCIENCE LTD, 2012) Paksoy, Turan; Pehlivan Yapıcı, Nimet; Kahraman, Cengiz
Distribution channel management not only consists of choosing distribution channels. In fact, probably the most difficult phase of the distribution management starts after this choice. Determining an appropriate organization strategy for distribution channel management is like a problem of concern to marketing practitioners and academics as well in this phase. In this study, the organization strategy of distribution channel management is developed using fuzzy analytic hierarchy process (FAHP) and hierarchical fuzzy TOPSIS (HFTOPSIS) for an edible-vegetable oils manufacturer firm operating in Turkey. The company distributes its products all over the country. Due to the complex structure of the distribution network, the company wants to decide the organization strategy to manage the distribution channels. In this paper, the methods of FAHP and HFTOPSIS for evaluating and selecting among the five organization strategy models for distribution channel management of vegetable oil manufacturer have been presented. The proposed models include determinants of distribution channel management for edible-vegetable oil industry; (i) customer profile, (ii) distributor reliability, (iii) the position of competitors in market, and (iv) managerial and financial perspective. Using FAHP and HFTOPSIS, hybrid based strategy (KBS), which has the greatest desirability index value after the evaluation among the five alternatives is found as the best choice. Thus, the case of the vegetable oil manufacturer company provides the researchers and practitioners to understand in a better way the importance of developing organization strategy in channel management from a practical point of view.
Job Scheduling in Virtual Manufacturing Cells With Lot-Streaming Strategy: A New Mathematical Model Formulation and a Genetic Algorithm Approach
(Taylor & Francis Ltd, 2012) Kesen, S. E.; Gungor, Z.
This paper discusses the job scheduling problem in virtual manufacturing cells (VMCs) with the objective of makespan minimization. In the VMC scheduling problem, each job undergoes different processing routes and there is a set of machines to process any operation. Jobs are produced in lot and lot-streaming is permitted. In addition, machines are distributed through the facility, which raises the travelling time issue. For this reason, the decisions are machine assignments, starting times and sub-lot sizes of the operations. We develop a new Mixed Integer Linear Programming (MILP) formulation that considers all aspects of the problem. Owing to the intractability matter, it is unlikely that the MILP could provide solutions for big-sized instances within a reasonable amount of time. We therefore present a Genetic Algorithm (GA) with a new chromosome structure for the VMC environment. Based on a wide range of examinations, comparative results show that GA is quite favourable and that it obtains the optimum solution for any of the instances in the case where sub-lot number equals 1.
hGA: Hybrid Genetic Algorithm in Fuzzy Rule-based Classification Systems for High-dimensional Problems
(Elsevier Science Bv, 2012) Kizilkaya Aydogan, Emel; Karaoglan, Ismail; Pardalos, Panos M.
The aim of this work is to propose a hybrid heuristic approach (called hGA) based on genetic algorithm (GA) and integer-programming formulation (IPF) to solve high dimensional classification problems in linguistic fuzzy rule-based classification systems. In this algorithm, each chromosome represents a rule for specified class, GA is used for producing several rules for each class, and finally IPF is used for selection of rules from a pool of rules, which are obtained by GA. The proposed algorithm is experimentally evaluated by the use of non-parametric statistical tests on seventeen classification benchmark data sets. Results of the comparative study show that hGA is able to discover accurate and concise classification rules. Published by Elsevier B.V.
Fuzzy Acceptance Sampling and Characteristic Curves
(Atlantıs Press, 2012) Turanoğlu, Ebru; Kaya, İhsan; Kahraman, Cengiz
Acceptance sampling is primarily used for the inspection of incoming or outgoing lots. Acceptance sampling refers to the application of specific sampling plans to a designated lot or sequence of lots. The parameters of acceptance sampling plans are sample sizes and acceptance numbers. In some cases, it may not be possible to define acceptance sampling parameters as crisp values. These parameters can be expressed by linguistic variables. The fuzzy set theory can be successfully used to cope with the vagueness in these linguistic expressions for acceptance sampling. In this paper, the main distributions of acceptance sampling plans are handled with fuzzy parameters and their acceptance probability functions are derived. Then the characteristic curves of acceptance sampling are examined under fuzziness. Illustrative examples are given.
Fuzzy Multi-Objective Optimization of a Green Supply Chain Network with Risk Management that Includes Environmental Hazards
(TAYLOR & FRANCIS INC, 2012) Paksoy, Turan; Yapıcı Pehlivan, Nimet; Özceylan, Eren
Among the leading environmental risks, global climate alteration has become one of the most important controversial issues. Greenhouse gas emissions (CO2, methane, etc.) and air pollution have motivated a need to develop and improve environmental management strategies. As a consequence, environmental sanctions are forcing commercial enterprises to re-consider and re-design supply chain processes in a green way. This article provides a multi-objective model to design a closed-loop supply chain (CLSC) network in a green framework. Our first and second objectives are to minimize all the transportation costs for the supply chain's forward and reverse logistics; the third objective is to minimize total CO2 emissions; the fourth objective is to encourage customers to use recyclable materials as an environmental practice. To provide more realistic modeling by treating the uncertainty in decision-makers' objectives, fuzzy modeling is used in this study. The model is explained and tested via fulfilling a numerical example. In scenario analyses, analytic hierarchy process (AHP), fuzzy AHP (F-AHP), and fuzzy TOPSIS (F-TOPSIS) approaches were applied and compared to evaluate different objectives to guide decision-makers.
Revised Multi-Choice Goal Programming for Multi-Period, Multi-Stage Inventory Controlled Supply Chain Model With Popup Stores in Guerrilla Marketing
(Elsevier Science Inc, 2010) Paksoy, Turan; Chang, Ching-Ter
In this paper, we consider a supply chain network design problem with popup stores which can be opened for a few weeks or months before closing seasonally in a marketplace. The proposed model is multi-period and multi-stage with multi-choice goals under inventory management constraints and formulated by 0-1 mixed integer linear programming. The design tasks of the problem involve the choice of the popup stores to be opened and the distribution network design to satisfy the demand with three multi-choice goals. The first goal is minimization of the sum of transportation costs in all stages; the second is to minimization of set up costs of popup stores; and the third goal is minimization of inventory holding and backordering costs. Revised multi-choice goal programming approach is applied to solve this mixed integer linear programming model. Also, we provide a real-world industrial case to demonstrate how the proposed model works.
Renewable Energy System Selection Based on Computing With Words
(Atlantis Press, 2010) Kahraman, Cengiz; Kaya, İhsan; Çebi, Selçuk
Renewable energy is the energy generated from natural resources such as sunlight, wind, rain, tides and geothermal heat. Turkey has a great renewable energy potential with its natural resources such as biomass, geothermal, hydropower, solar, and wind. Selection among energy alternatives is a multicriteria decision-making problem with conflicting and interactive criteria. In this paper, the best energy alternative of Turkey is determined by taking into interactions among criteria by using Choquet integral methodology.
Optimizing a Supply Chain Network With Emission Trading Factor
(Academic Journals, 2010) Paksoy, Turan
In the supply chain, producers try to plan their raw materials and final products with the production and delivery system for control of their flow, and this planning has to start from the purchase of the raw material for production to the delivery stage. Supply chain management and optimization is a promising aspect of enterprises and an exiting research area. Recently, there is a growing interest in supply chain design due to environmental impacts. It has become a necessity for the study to consider in the costs of transportation, the factor of environmental costs as social costs. In this paper, a new mixed integer mathematical model for a supply chain system is proposed. The chain system consists of two echelons and includes six suppliers, six manufacturers and six customer zones with six time period. The developed and proposed model provides the optimal values of transportation amounts of the purchased, manufactured and delivered raw material, while solving the location problem of each actor. We consider different trucks used for transporting according to their rental fees and CO(2) emission amounts. Also, we integrate a constraint of CO(2) emission quota into the supply chain as an environmental impact. The proposed model is validated by using hypothetical data and the results are discussed.
Multiprocessor Task Scheduling in Multistage Hybrid Flow-Shops: A Parallel Greedy Algorithm Approach
(ELSEVIER, 2010) Kahraman, Cengiz; Engin, Orhan; Kaya, İhsan; Öztürk, R. Elif
Hybrid flow shop scheduling problems have a special structure combining some elements of both the flow shop and the parallel machine scheduling problems. Multiprocessor task scheduling problem can be stated as finding a schedule for a general task graph to execute on a multiprocessor system so that the schedule length can be minimized. Hybrid Flow Shop Scheduling with Multiprocessor Task (HFSMT) problem is known to be NP-hard. In this study we present an effective parallel greedy algorithm to solve HFSMT problem. Parallel greedy algorithm (PGA) is applied by two phases iteratively, called destruction and construction. Four constructive heuristic methods are proposed to solve HFSMT problems. A preliminary test is performed to set the best values of control parameters, namely population size, subgroups number, and iteration number. The best values of control parameters and operators are determined by a full factorial experimental design using our PGA program. Computational results are compared with the earlier works of Oguz et al. [1,3], and Oguz [2]. The results indicate that the proposed parallel greedy algorithm approach is very effective in terms of reduced total completion time or makespan (C-max) for the attempted problems.
Integrated Line Balancing to Attain Shojinka in a Multiple Straight Line Facility
(Taylor & Francis Ltd, 2010) Gökçen, Hadi; Kara, Yakup; Atasagun, Yakup
Traditional straight assembly lines are still one of the most important elements and an important fact of today's production systems. If applicable, a company can combine its multiple straight assembly lines and obtain many advantages of Shojinka more or less. This paper analyses a new problem - integrated balancing of multiple straight assembly lines (MSLB) to attain Shojinka in a multiple straight assembly line facility. The MSLB problem is built on the concept that it could be possible for a company to obtain the advantages of Shojinka even if the company has not adopted the U-shaped line layout. Three connectivity types are suggested to integrate multiple assembly lines. A binary integer formulation for integrated balancing of multiple assembly lines is developed. The objective of the proposed formulation is to minimise the total number of workstations required in the assembly facility. The formulation is explained and validated using some illustrative examples. The proposed approach provides flexibility to minimise the total idle times of the lines and total number of workstations that are required in the assembly line facility.
Fuzzy Process Capability Analysis and Applications
(Springer-Verlag Berlin, 2010) Kahraman, Cengiz; Kaya, İhsan
Process capability indices (PCIs) are very useful statistical analysis tools to summarize process' dispersion and location through process capability analysis (PCA). PCIs are mainly used in industry to measure the capability of a process to produce products meeting specifications. Traditionally, the specifications are defined as crisp numbers. Sometimes, the specification limits (SLs) can be expressed in linguistic terms. Traditional PCIs cannot be applied for this kind of data. There are also some limitations which prevent a deep and flexible analysis because of the crisp definition of SLs. In this chapter, the fuzzy set theory is used to add more sensitiveness to PCA including more information and flexibility. The fuzzy PCA is developed when the specifications limits are represented by triangular or trapezoidal fuzzy numbers. Crisp SLs with fuzzy normal distribution are used to calculate the fuzzy percentages of conforming (FCIs) and nonconforming (FNCIs) items by taking into account fuzzy process mean, (mu) over tilde and fuzzy variance, (sigma) over tilde (2). Then fuzzy SLs are used together with (mu) over tilde and (sigma) over tilde (2) to produce fuzzy PCIs (FPCIs). FPCIs are analyzed under the existence of correlation and thus fuzzy robust process capability indices are obtained. Then FPCIs are improved for six sigma approach. And additionally, process accuracy index is analyzed under fuzzy environment. The results show that fuzzy estimations of PCIs have much more treasure to evaluate the process when it is compared with the crisp case.
Fuzzy and Grey Forecasting Techniques and Their Applications in Production Systems
(Springer-Verlag Berlin, 2010) Kahraman, Cengiz; Yavuz, Mesut; Kaya, İhsan
Forecasting is an important part of decision making as many of our decisions are based on predictions of future unknown events. Forecast is an interesting research topic that has received attention from many researchers in the past several decades. Forecasting has many application areas including but not limited to stock markets, futures markets, enrollments of a school, demand of a product and/or service. Management needs to reduce the risks associated with decision-making, which can be done by anticipating the future more clearly. Accurate forecasts are therefore essential for risk reduction. Forecasting provides critical inputs to various manufacturing-related processes, such as production planning, inventory management, capital budgeting, purchasing, work-force scheduling, resource allocation and other important parts of the production system operation. Accurate forecasts are crucial for successful manufacturing and can lead to considerable savings when implemented efficiently. Forecasting literature contains a large variety of techniques from simple regression to complex metaheuristics such as neural networks and genetic algorithms. Fuzzy set theory is also another useful tool to increase forecast efficiency and effectiveness. This chapter summarizes and classifies forecasting techniques based on crisp logic, fuzzy logic and the grey theory. The chapter also presents numerical examples of fuzzy simple linear regression and grey forecasting methodology.

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