Browsing by Author "Eliiyi, Deniz Türsel"

Now showing 1 - 15 of 15

Citation - WoS: 10
Citation - Scopus: 13
A Bus Crew Scheduling Problem with Eligibility Constraints and Time Limitations
(ELSEVIER SCIENCE BV, 2017) Hande Oztop; Ugur Eliiyi; Deniz Tursel Eliiyi; Levent Kandiller; Öztop, Hande; Kandiller, Levent; Eliiyi, Uǧur; Eliiyi, Deniz Türsel; HB Celikoglu; AH Lav; MA Silgu
In this study we consider a real life crew scheduling problem (CSP) of a public bus transportation authority where the objective is to determine the optimal number of different types of crew members with a minimum cost that cover a given set of tasks regarding working and spread time limitations. Each driver has a spread time limit from the start time to the end time of his/her shift including the idle times. Additionally a driver cannot exceed the maximum total working time limit. The processing times of the tasks assigned to each driver are included in his/her working time as well as the sequence-dependent setup times. As our study is inspired from a real life CSP the tasks can require different types of vehicles that require different crew capabilities. Therefore there are several crew classes based on the competencies required to use certain vehicle types inducing eligibility constraints in the problem. We formulate a Tactical Fixed Job Scheduling Problem based binary programming model for the problem. In the formulation we consider only processing times of tasks as working time. In order to avoid defining an additional sequence control variable that explodes the model size and in turn ruins solution performance we develop an iterative valid inequality generation scheme which eliminates task sequences exceeding the total working time when setup times are included. The performance of the developed model is investigated through a comprehensive experimentation and the numerical results are reported. The results show that our optimal seeking solution procedure is quite effective in terms of solution time for instances with up to 120 tasks. (C) 2017 The Authors. Published by Elsevier B.V.
Citation - WoS: 9
Citation - Scopus: 9
A reward-based algorithm for the stacking of outbound containers
(Elsevier B.V., 2017) Sel Ozcan; D. T. Eliiyi; Ozcan, Sel; Eliiyi, Deniz Türsel
As global trade increases container transshipment activities increase rapidly. Therefore high competition among container terminals has emerged. The decision for good stacking positions for containers plays a critical role on the performance of a container terminal since it influences the productivity of the terminal in a strong sense. In this study we focus on the minimization of the berthing time of vessels by improving the stacking operations through minimization of non-value-added handling operations of containers which is called reshuffling as well as the traveling time of the cranes operating at the storage yard. Most of the containers in the container terminal we focus are outbound which are transported into the container terminal via external trucks and stored in the stacking yard until they are loaded onto vessels. We propose a reward-based algorithm for the stacking of outbound containers by taking the following four components into consideration, container's distance to the closest RTGC RTGC's workload the number of stacked containers at the neighborhood bays and the current height of the stacks at the storage yard. The inputs of the algorithm include the relevant information of the container to be stacked that are just entered into the terminal gate current usage information of the storage yard and the current positions of the yard cranes. The proposed stacking strategy is in implementation phase to one of the container terminals in Izmir. The results seem to be promising when compared to the current randomized stacking strategy in the container terminal. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Citation - Scopus: 2
An alternative MILP model for makespan minimization on assembly lines
(SPRINGER HEIDELBERG, 2017) Sel Ozcan; Deniz Tursel Eliiyi; Levent Kandiller; Kandiller, Levent; Ozcan, Sel; Eliiyi, Deniz Türsel
The Simple Assembly Line Balancing Problem-2 (SABLP-2) is defined as partitioning the tasks among stations in order to minimize the cycle time given the number of stations. SALBP-2 reduces to the identical parallel machine scheduling problem with makespan minimization (P-m parallel to C-max) when precedence relations are ignored providing a lower bound. In a certain layout setting tasks revisiting the same station over consecutive tours might be preferable when the sole objective is to minimize the makespan of producing the order quantity. In this study the tradeoff between the makespans obtained from SALBP-2 and (P-m parallel to C-max) as a function of order quantity is analyzed. A piecewise linear concave makespan function is observed. We developed an alternative model formulation and an iterative solution scheme for makespan minimization for all possible order quantities. The results of our computational experiment indicate that SALBP-2 outperforms for small order quantities whereas (P-m parallel to C-max) yields the best results for larger order quantities. However there is a certain range of order quantity for which the proposed model dominates the other two. Our results are validated in benchmark instances.
Citation - WoS: 50
Citation - Scopus: 56
An energy-efficient permutation flowshop scheduling problem
(Elsevier Ltd, 2020) Hande Oztop; M. Fatih Tasgetiren; D. T. Eliiyi; Quanke Pan; Levent Kandiller; Tasgetiren, M. Fatih; Öztop, Hande; Pan, Quan-Ke; Kandiller, Levent; Eliiyi, Deniz Türsel
The permutation flowshop scheduling problem (PFSP) has been extensively explored in scheduling literature because it has many real-world industrial implementations. In some studies multiple objectives related to production efficiency have been considered simultaneously. However studies that consider energy consumption and environmental impacts are very rare in a multi-objective setting. In this work we studied two contradictory objectives namely total flowtime and total energy consumption (TEC) in a green permutation flowshop environment in which the machines can be operated at varying speed levels corresponding to different energy consumption values. A bi-objective mixed-integer programming model formulation was developed for the problem using a speed-scaling framework. To address the conflicting objectives of minimizing TEC and total flowtime the augmented epsilon-constraint approach was employed to obtain Pareto-optimal solutions. We obtained near approximations for the Pareto-optimal frontiers of small-scale problems using a very small epsilon level. Furthermore the mathematical model was run with a time limit to find sets of non-dominated solutions for large instances. As the problem was NP-hard two effective multi-objective iterated greedy algorithms and a multi-objective variable block insertion heuristic were also proposed for the problem as well as a novel construction heuristic for initial solution generation. The performance of the developed heuristic algorithms was assessed on well-known benchmark problems in terms of various quality measures. Initially the performance of the algorithms was evaluated on small-scale instances using Pareto-optimal solutions. Then it was shown that the developed algorithms are tremendously effective for solving large instances in comparison to time-limited model. © 2020 Elsevier B.V. All rights reserved.
Citation - WoS: 9
Citation - Scopus: 12
Artificial Intelligence Approaches to Estimate the Transport Energy Demand in Turkey
(Springer Science and Business Media Deutschland GmbH, 2021) Mert Sinan Turgut; Uǧur Eliiyi; Oğuz Emrah Turgut; Erdinc Oner; D. T. Eliiyi; Turgut, Oguz Emrah; Eliiyi, Uğur; Turgut, Mert Sinan; Öner, Erdinç; Eliiyi, Deniz Türsel
In this study eight parameters are selected and their historical data are collected to predict the future of the energy demand of Turkey. The initial eight parameters were the gross domestic product (GDP) of Turkey average annual US crude oil price (COP) inflation for Turkey in percentages (INF) the population of Turkey total vehicle travel in kilometers for Turkey total amount of goods transported on motorways employment for Turkey and trade of Turkey. However after these eight parameters data are analyzed using Pearson and Spearman correlation methods it is found out that five of these parameters are highly correlated. The remaining three parameters are the GDP of Turkey COP and INF for Turkey. Afterward five separate scenarios are developed to forecast the future of the energy demand of Turkey. The first two scenarios involve the third- and fourth-order polynomial fitting the third and fourth scenarios employ static and recurrent neural networks and the fifth scenario utilizes autoregressive models to predict the future energy demand of Turkey. The efficient hybridization of the seagull optimization and very optimistic method of minimization metaheuristic algorithms is carried out to achieve the polynomial fitting of the data. The optimization performance of the hybrid algorithm is assessed by applying the algorithm on benchmark optimization problems and comparing the results with that of some other metaheuristic optimizers. Moreover it is seen that the forecasts of the first scenario agree well with the Ministry of the Energy and Natural Resources estimates. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 33
Citation - Scopus: 37
Ensemble of metaheuristics for energy-efficient hybrid flowshops: Makespan versus total energy consumption
(Elsevier B.V., 2020) Hande Oztop; M. Fatih Tasgetiren; Levent Kandiller; D. T. Eliiyi; Liang Gao; Tasgetiren, M. Fatih; Gao, Liang; Öztop, Hande; Kandiller, Levent; Eliiyi, Deniz Türsel
Due to its practical relevance the hybrid flowshop scheduling problem (HFSP) has been widely studied in the literature with the objectives related to production efficiency. However studies regarding energy consumption and environmental effects have rather been limited. This paper addresses the trade-off between makespan and total energy consumption in hybrid flowshops where machines can operate at varying speed levels. A bi-objective mixed-integer linear programming (MILP) model and a bi-objective constraint programming (CP) model are proposed for the problem employing speed scaling. Since the objectives of minimizing makespan and total energy consumption are conflicting with each other the augmented epsilon (ε)-constraint approach is used for obtaining the Pareto-optimal solutions. While close approximations for the Pareto-optimal frontier are obtained for small-sized instances sets of non-dominated solutions are obtained for large instances by solving the MILP and CP models under a time limit. As the problem is NP-hard two variants of the iterated greedy algorithm a variable block insertion heuristic and four variants of ensemble of metaheuristic algorithms are also proposed as well as a novel constructive heuristic. The performances of the proposed seven bi-objective metaheuristics are compared with each other as well as the MILP and CP solutions on a set of well-known HFSP benchmarks in terms of cardinality closeness and diversity of the solutions. Initially the performances of the algorithms are tested on small-sized instances with respect to the Pareto-optimal solutions. Then it is shown that the proposed algorithms are very effective for solving large instances in terms of both solution quality and CPU time. © 2020 Elsevier B.V. All rights reserved.
Heterojen filolu dağıtım, toplama ve zaman pencereli araç rotalama problemi için adaptif geniş komşuluk arama algoritması
(2016) Özsakallı, Gökberk; Eliiyi, Deniz Türsel
In this thesis, a heterogeneous vehicle routing problem with time windows and simultaneous pick-up and delivery, which has wide application areas, is handled. Three different types of mathematical models are proposed to formulate the problem. The first one is based on Miller-Tucker-Zemlin (1960) constraints. The other two are based on flow decision variables. To the best of our knowledge, the problem has not been studied in the vehicle routing literature. A new set of benchmark instances is also generated to compare lower bounds of mathematical models. The flow variable-based mathematical models provide the best results based on the computational experiments. As the mathematical models can solve only small sized instances, a heuristic algorithm based on Adaptive Large Neighborhood Search is proposed to solve larger real world instances. When the proposed heuristic algorithm and the mathematical models are compared, it is observed that the algorithm finds the optimal solution in most of the test instances. On the average, the algorithm finds better solutions than the mathematical models. The algorithm is also compared with a simple insertion heuristic for large instances, and is found to obtain much better solutions than the simple insertion heuristic. The proposed algorithm is not only stable in terms of solution quality, but also robust in terms of computation time. The proposed heuristic algorithm can be used in everyday logistics operations to obtain very fast and high quality solutions.
Citation - WoS: 9
Citation - Scopus: 14
Iterated greedy algorithms for the hybrid flowshop scheduling with total flow time minimization
(Association for Computing Machinery Inc acmhelp@acm.org, 2018) Hande Oztop; D. T. Eliiyi; M. Fatih Tasgetiren; Quanke Pan; Tasgetiren, M. Fatih; Fatih Tasgetiren, M.; Öztop, Hande; Pan, Quan-Ke; Eliiyi, Deniz Türsel
1 The hybrid flosshop scheduling problem (HFSP) has been extensively studied in the literature due to its complexity and real-life applicability. Various exact and heuristic algorithms have been developed for the HFSP and most consider makespan as the only criterion. The studies on HFSP sith the objective of minimizing total flos time have been rather limited. This paper presents a mathematical model and efficient iterated greedy algorithms IG and IGALL for the HFSP sith total flos time criterion. In order to evaluate the performance of the proposed IG algorithms the sell-knosn HFSP benchmark suite from the literature is used. As the problem is NP-hard the proposed mathematical model is solved for all 87 instances under a time limit on CPLEX. Optimal results are obtained for some of these instances. The performance of the IG algorithms is measured by comparisons sith these time-limited CPLEX results of the mathematical model. Computational results shos that the proposed IG algorithms perform very sell in terms of solution time and quality. To the best of our knosledge for the first time in the literature the results of flos time criterion have been reported for the HFSP benchmark suite. © 2018 Elsevier B.V. All rights reserved.
Karışamayan ürünler için çok kompartımanlı araç rotalama problemi
(2016) Taşar, Bahar; Kandiller, Levent; Eliiyi, Deniz Türsel
This thesis focuses on a special category of distribution problems for the case of incompatible products. To satisfy different type of demands with minimum logistics costs, incompatible products are carried on the same vehicle but in different compartments. The scope of this study is to explore new mathematical models for the corresponding Multi-Compartment Vehicle Routing Problem (MCVRP) and its variants. While there exists a vast amount of Vehicle Routing Problem (VRP) literature covering several variants, the MCVRP is still open for research. Our study is motivated by a real life instance of a livestock feed distribution system, where each livestock farm demands one type of feed from a single depot. We consider some variants of the MCVRP, as multiple trips of vehicles and the splitting of demand. A taxonomic framework for VRP literature is also suggested. A general mathematical model, and its variants are formulated. A computational experiment is designed for testing the performance of the developed models. Exact solution schemes are evaluated for small sized problem instances, whereas heuristic algorithms are proposed for larger instances. Our results indicate that the proposed methodology is applicable to real life logistics problems such as food, fuel and other chemical distribution.
Konteyner taşımacılığında dinamik ve senkronize intermodal taşıma planları tasarımı
(2018) Tatari, Sel Özcan; Eliiyi, Deniz Türsel
In this thesis, we present a mixed integer linear programming model for the operational level cargo allocation and vessel scheduling problem, where flow-dependent port-stay lengths, transit times and transshipment schedule synchronizations are considered. The proposed model aims to assign shipments to routes to minimize total tardiness, and construct vessel partial schedules for establishing coordination with port authorities to meet the berthing time windows. In addition to mathematical model, novel valid inequalities are proposed, and a benders decomposition algorithm is implemented. Algorithm performances are tested on real-life problem instances. The results show that benders decomposition with valid inequalities yields the best performance on the test instances. The thesis is further extended with the consideration of instant terminal port performances, and an integrated solution framework is proposed for this dynamic problem. The thesis study aims to contribute to both the practitioners and to the state-of-the-art literature.
Konteyner terminallerinde kıyı ve saha operasyonlarının bütünleşik optimizasyonu
(2018) Kızılay, Damla; Eliiyi, Deniz Türsel
Although operations in container terminals are highly interdependent, they are traditionally optimized by decomposing the overall problem into a sequence of smaller subproblems, each of which focuses on a single operation. Recent studies, however, have demonstrated the need and potential of optimizing these interdependent operations jointly. This thesis proposes the integrated port container terminal problem that considers the joint optimization of quay crane assignment and scheduling, yard crane assignment and scheduling, and yard location assignments. The proposed problem minimizes vessel turnover times and maximizes the terminal throughput, which are key economic drivers in terminal operations. It also considers inbound and outbound containers simultaneously and models safety distance and interference constraints between quay cranes. To solve the integrated problem, the thesis proposes MIP and CP models as well as a heuristic algorithm. Computational results show that the MIP model only solves small instances, while the CP model finds optimal solutions in reasonable times for realistic instances derived from actual container terminal operations in Turkey. The CP model is also be generalized into a goal-programming approach to minimize the number of yard trucks in a second stage. Also, an adaptive large neighborhood search heuristic is employed to obtain solutions in short CPU times and to improve some cases in which the CP model cannot find optimal results. Overall, the heuristic algorithm is performing well for the problem and is very competitive with the exact models.
Citation - WoS: 79
Citation - Scopus: 94
Metaheuristic algorithms for the hybrid flowshop scheduling problem
(PERGAMON-ELSEVIER SCIENCE LTD, 2019) Hande Oztop; M. Fatih Tasgetiren; Deniz Tursel Eliiyi; Quan-Ke Pan; Tasgetiren, M. Fatih; Fatih Tasgetiren, M.; Öztop, Hande; Pan, Quan-Ke; Eliiyi, Deniz Türsel
The hybrid flowshop scheduling problem (HFSP) has been widely studied in the literature as it has many real-life applications in industry. Even though many solution approaches have been presented for the HFSP with makespan criterion studies on HFSP with total flow time minimization have been rather limited. This study presents a mathematical model four variants of iterated greedy algorithms and a variable block insertion heuristic for the HFSP with total flow time minimization. Based on the well-known NEH heuristic an efficient constructive heuristic is also proposed and compared with NEH. A detailed design of experiment is carried out to calibrate the parameters of the proposed algorithms. The HFSP benchmark suite is used for evaluating the performance of the proposed methods. As there are only 10 large instances in the current literature further 30 large instances are proposed as new benchmarks. The developed model is solved for all instances on CPLEX under a time limit and the performances of the proposed algorithms are assessed through comparisons with the results from CPLEX and the two best-performing algorithms in literature. Computational results show that the proposed algorithms are very effective in terms of solution time and quality. Additionally the proposed algorithms are tested on large instances for the makespan criterion which reveal that they also perform superbly for the makespan objective. Especially for instances with 30 jobs the proposed algorithms are able to find the current incumbent makespan values reported in literature and provide three new best solutions. (C) 2019 Elsevier Ltd. All rights reserved.
Citation - Scopus: 10
Optimal buffer allocation for serial production lines using heuristic search algorithms: A comparative study
(Inderscience Publishers, 2019) L. Demir; Alexandros C. Diamantidis; D. T. Eliiyi; Michael E.J. O'Kelly; Semra Tunali; Demir, Leyla; O'Kelly, M.E.J.; Diamantidis, Alexandros C.; Tunali, Semra; Eliiyi, Deniz Türsel
The buffer allocation problem (BAP) is one of the major optimisation problems faced by production system designers. BAP is widely studied in the literature since buffers have a great impact on efficiency of production lines. This paper deals with buffer allocation problem and compares the performance of three heuristic search algorithms namely myopic algorithm (MA) degraded ceiling (DC) and adaptive tabu search (ATS) with respect to both throughput maximisation and also computational time. To generalise experimental findings the experiments have been conducted both for reliable and also unreliable serial production lines over various sizes of problem instances. It is hoped that the findings of this research study can serve as a guideline for the decision makers while designing and operating production lines. © 2020 Elsevier B.V. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 6
ROUTE OPTIMIZATION FOR THE DISTRIBUTION NETWORK OF A CONFECTIONARY CHAIN
(SVENCILISTE U ZAGREBU FAKULTET PROMETNIH ZNANOSTI, 2015) Anil Inanli; Basak Unsal; Deniz Tursel Eliiyi; Ünsal, Başak; İnanli, Anil; Eliiyi, Deniz Türsel
This study considers the distribution network of a well-known perishable food manufacturer and its franchises in Turkey. As the countrywide number of stores is increasing fast the company is facing problems due to its central distribution of products from a single factory. The objective is to decrease the cost of transportation while maintaining a high level of customer satisfaction. Hence the focus is on the vehicle routing problem (VRP) of this large franchise chain within each city. The problem is defined as a rich VRP with heterogeneous fleet site-dependent and compartmentalized vehicles and soft/hard time windows. This NP-hard problem is modelled and tried with real data on a commercial solver. A basic heuristic procedure which can be used easily by the decision makers is also employed for obtaining quick and high-quality solutions for large instances.
Toplu taşımada araç ve sürücü çizelgeleme problemleri
(2016) Öztop, Hande; Kandiller, Levent; Eliiyi, Deniz Türsel
Bu tezde, toplu taşıma operasyonlarının araç ve sürücü çizelgeleme aşamaları, bir toplu taşıma idaresinin gerçek hayat probleminden esinlenilerek çalışılmıştır. Problemde amaç önceden belirlenmiş seferleri ve araç atamalarından kaynaklanacak ölü kilometre seferlerini, sürücülerin toplam çalışma ve vardiya sürelerini dikkate alarak taşımacılığı minimum maliyetle karşılamak için gereken farklı tipteki araç ve sürücülerin sayısını optimal şekilde belirlemektir. Her iki alt problem için tamsayılı programlama modelleri geliştirilmiştir. Sürücü çizelgelemede, toplam çalışma süresini aşan görev sıralamalarını elemek üzere tekrarlamalı geçerli eşitsizlik yaratma yöntemi geliştirilmiştir. Her alt problem için geliştirilen çözüm yöntemlerinin performansları detaylı deneylerle araştırılmıştır ve sonuçlar önerilen optimal arama çözüm yöntemlerinin çözüm süreleri açısından oldukça etkili olduğunu göstermiştir. Bunun yanında, bütüncül problem için sıralı ve entegre olmak üzere iki yaklaşım önerilmiştir. Entegre yaklaşımda tamsayılı bir programlama modeli geliştirilmiş ve küçük boyutlu örnek problemler optimal olarak çözülmüştür. Ancak üstel artan çözüm süreleri nedeniyle büyük boyutlu problemler makul süreler içerisinde çözülememiştir. Bu nedenle araç ve sürücü çizelgeleme problemleri için geliştirilmiş olan tamsayılı programlama modellerinin sırayla çözüldüğü bir sıralı yaklaşım önerilmiştir. Bu yaklaşımın performansı kapsamlı sayısal deneyle araştırılmıştır ve sonuçlar sıralı yaklaşımın en fazla 120 sefere sahip örnekler için oldukça etkin ve verimli olduğunu göstermiştir. Ayrıca sıralı yaklaşım küçük boyutlu örnekler üzerinden entegre yaklaşım ile kıyaslanmıştır ve sonuçlar sıralı yaklaşımın çok makul sürede optimale yakın sonuçlar bulmada oldukça etkin olduğunu göstermiştir.