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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Measuring the quality of discrete representations of efficient sets in multiple objective mathematical programming(Springer, 2000) N/A; Department of Business Administration; Sayın, Serpil; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 6755One way of solving multiple objective mathematical programming problems is ending discrete representations of the efficient set. A modified goal of finding good discrete representations of thr efficient set would contribute to the practicality of vector maximization algorithms. We define coverage, uniformity and cardinality as the three attributes of quality of discrete representations and introduce a framework that includes these attributes in which discrete representations can be evaluated, compared to each other, and judged satisfactory or unsatisfactory by a Decision Maker. We provide simple mathematical programming formulation that can he used to compute the coverage error of a given discrete representation. Our formulations are practically implementable when the problem under study is a multiobjective linear programming problem. We believe that the interactive algorithms along with the vector maximization methods can make use of our framework and its tools.Publication Metadata only Finite-capacity scheduling-based planning for revenue-based capacity management(Elsevier Science Bv, 1997) Department of Business Administration; Akkan, Can; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; N/AFinite-capacity scheduling can be argued to be a crucial component of revenue-based capacity management. In that case, one way to plan production is to reserve portions of capacity for incoming customer orders as they arrive, in real-time. In such a planning method, the way these work-orders are scheduled affects the useable capacity, due to fragmentation of the time-line. Assuming the work-orders are rejected if they cannot be inserted into the existing schedule, we develop heuristics to minimise the present-value of the cost of rejecting orders and inventory holding cost due to early completion. We perform simulation experiments to compare the performance of these heuristics in addition to some common heuristics used in practice.Publication Metadata only Overtime scheduling: an application in finite-capacity real-time scheduling(Taylor & Francis, 1996) Department of Business Administration; Akkan, Can; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; N/ANegotiating and meeting due-times for work-orders is often the most important concern of managers of manufacturing systems. We propose a new approach called overtime scheduling that determines on which work-centres, when and how much overtime is required to meet a requested due-time with minimum overtime cost. This method would be used as a part of a finite-capacity real-time scheduling and planning system. We propose a work-order insertion based approach, where a new work-order is scheduled without substantially changing the schedule of previously scheduled work-orders. Based on this approach, we characterise the solution space and present experimental results on the performances of several heuristics.Publication Metadata only An adaptive large neighborhood search algorithm for a selective and periodic inventory routing problem(Elsevier, 2014) Department of Business Administration; Department of Industrial Engineering; Department of Industrial Engineering; N/A; Aksen, Deniz; Kaya, Onur; Salman, Fatma Sibel; Tüncel, Özge; Faculty Member; Faculty Member; Faculty Member; Master Student; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Sciences; College of Engineering; Graduate School of Sciences and Engineering; 40308; 28405; 178838; N/AWe study a selective and periodic inventory routing problem (SPIRP) and develop an Adaptive Large Neighborhood Search (ALNS) algorithm for its solution. The problem concerns a biodiesel production facility collecting used vegetable oil from sources, such as restaurants, catering companies and hotels that produce waste vegetable oil in considerable amounts. The facility reuses the collected waste oil as raw material to produce biodiesel. It has to meet certain raw material requirements either from daily collection, or from its inventory, or by purchasing virgin oil. SPIRP involves decisions about which of the present source nodes to include in the collection program, and which periodic (weekly) routing schedule to repeat over an infinite planning horizon. The objective is to minimize the total collection, inventory and purchasing costs while meeting the raw material requirements and operational constraints. A single-commodity flow-based mixed integer linear programming (MILP) model was proposed for this problem in an earlier study. The model was solved with 25 source nodes on a 7-day cyclic planning horizon. In order to tackle larger instances, we develop an ALNS algorithm that is based on a rich neighborhood structure with 11 distinct moves tailored to this problem. We demonstrate the performance of the ALNS, and compare it with the MILP model on test instances containing up to 100 source nodes.Publication Metadata only A station model for continuous materials flow production systems(Taylor & Francis, 1997) Yeralan, S; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600This study develops a station model for continuous flow production systems. The most prominent use of the model is as a building block for a general and flexible decomposition method to analyse and design continuous materials flow production systems. Station breakdown and a finite capacity buffer are considered. Station inference caused by the blocking and starving phenomena is included in the station model. We assume that the time to station breakdown and station repair are exponentially distributed while the buffer is neither empty nor full. No restrictive assumptions are made about the distributions of the station breakdown and repair times when the station is blocked or starved, that is, while the buffer remains empty or remains full. The production rate and the expected level of the buffer are given in closed form. Numerical results that show the effects of the input parameters on the production rate along with an overview of the decomposition methods are presented.Publication Metadata only Health network mergers and hospital re-planning(Taylor & Francis, 2010) Yaman, H.; Department of Business Administration; Güneş, Evrim Didem; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51391This paper presents an integer programming formulation for the hospital re-planning problem which arises after hospital network mergers. The model finds the best re-allocation of resources among hospitals, the assignment of patients to hospitals and the service portfolio to minimize the system costs subject to quality and capacity constraints. An application in the Turkish hospital networks case is illustrated to show the implications of consolidation of health insurance funds on resource allocations and flow of patients in the system. Journal of the Operational Research Society (2010) 61, 275-283. doi: 10.1057/jors.2008.165 Published online 11 February 2009Publication Metadata only A mixed integer programming formulation for the l-maximin problem(Stockton Press, 2000) N/A; Department of Business Administration; Sayın, Serpil; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 6755In this paper, I present a mixed integer programming (MIP) formulation for the 1-maximin problem with rectilinear distance. The problem mainly appears in facility location while trying to locate an undesirable facility. The rectilinear distance is quite Commonly used in the location literature. Our numerical experiments show that one can solve reasonably large location problems using a standard MIP solver. We also provide a linear programming formulation that helps find an upper bound on the objective function value of the 1-maximin problem with any norm when extreme points of the feasible region are known. We discuss various extension alternatives for the MIP formulation.Publication Metadata only DNA sequencing by hybridization via genetic search(2006) Blazewicz, Jacek; Swiercz, Aleksandra; Weglarz, Jan; Department of Industrial Engineering; Oğuz, Ceyda; Faculty Member; Department of Industrial Engineering; College of Engineering; 6033An innovative approach to DNA sequencing by hybridization utilizes isothermic oligonucleotide libraries. In this paper, we demonstrate the utility of a genetic algorithm for the combinatorial portion of this new approach by incorporating characteristics of DNA sequencing by hybridization in addition to isothermic oligonucleotide libraries. Specialized crossover and mutation operators were developed for this purpose. After initial experiments for parameter adjustment, the performance of the genetic algorithm approach was evaluated with respect to previous methods in the literature. The results indicate that the proposed new approach is superior to previous approaches. The proposed new crossover operator that inherits some features of the structured weighted combinations might also be of value for some other combinatorial problems, including the traveling salesman problem.Publication Metadata only A bicriteria approach to the two-machine flow shop scheduling problem(Elsevier Science Bv, 1999) N/A; Department of Business Administration; Department of Business Administration; Sayın, Serpil; Karabatı, Selçuk; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; College of Administrative Sciences and Economics; 6755; 38819In this paper we address the problem of minimizing makespan and sum of completion times simultaneously in a two-machine flow shop environment. We formulate the problem as a bicriteria scheduling problem, and develop a branch-and-bound procedure that iteratively solves restricted single objective scheduling problems until the set of efficient solutions is completely enumerated. We report computational results, and explore certain properties of the set of efficient solutions. We then discuss their implications for the Decision Maker.Publication Metadata only Parallel machine scheduling with tool loading: a constraint programming approach(Taylor & Francis Ltd, 2018) Hnich, Brahim; Ozpeynirci, Selin; Gökgür, Burak; PhD Student; Graduate School of Business; 181004This paper presents constraint programming models that aim to solve scheduling and tool assignment problems in parallel machine environments. There are a number of jobs to be processed on parallel machines. Each job requires a set of tools, but limited number of tools are available in the system due to economic restrictions. The problem is to assign the jobs and the required tools to machines and to determine the schedule so that the makespan is minimised. Three constraint programming models are developed and compared with existing methods described in the literature.