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ERDOĞAN, Güneş

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Güneş

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Now showing 1 - 9 of 9
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    Formulations and branch-and-cut algorithms for the generalized vehicle routing problem
    (Informs, 2011-08) Bektaş, T.; Erdoğan, Güneş; Ropke, S.; Industrial Engineering; ERDOĞAN, Güneş
    The generalized vehicle routing problem (GVRP) consists of finding a set of routes for a number of capacitated vehicles on a graph where the vertices are partitioned into clusters with given demands, such that the total cost of travel is minimized and all demands are met. This paper describes and compares four new integer linear programming formulations for the GVRP, two based on multicommodity flow and the other two based on exponential-size sets of inequalities. Branch-and-cut algorithms are proposed for the latter two. Computational results on a large set of instances are presented.
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    Two classes of quadratic assignment problems that are solvable as linear assignment problems
    (Elsevier, 2011-08) Erdoğan, Güneş; Tansel, B. Ç.; Industrial Engineering; ERDOĞAN, Güneş
    The Quadratic Assignment Problem is one of the hardest combinatorial optimization problems known. We present two new classes of instances of the Quadratic Assignment Problem that can be reduced to the Linear Assignment Problem and give polynomial time procedures to check whether or not an instance is an element of these classes.
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    ArticlePublicationOpen Access
    Scheduling ambulance crews for maximum coverage
    (Palgrave MacMillan, 2010-04) Erdoğan, Güneş; Erkut, Erhan; Ingolfsson, A.; Laporte, G.; Business Administration; Industrial Engineering; ERDOĞAN, Güneş; ERKUT, Erhan
    This paper addresses the problem of scheduling ambulance crews in order to maximize the coverage throughout a planning horizon. The problem includes the subproblem of locating ambulances to maximize expected coverage with probabilistic response times, for which a tabu search algorithm is developed. The proposed tabu search algorithm is empirically shown to outperform previous approaches for this subproblem. Two integer programming models that use the output of the tabu search algorithm are constructed for the main problem. Computational experiments with real data are conducted. A comparison of the results of the models is presented.
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    A branch-and-cut algorithm for solving the non-preemptive capacitated swapping problem
    (Elsevier, 2010-08-06) Erdoğan, Güneş; Cordeau, J.-F.; Laporte, G.; Industrial Engineering; ERDOĞAN, Güneş
    This paper models and solves a capacitated version of the Non-Preemptive Swapping Problem. This problem is defined on a complete digraph , at every vertex of which there may be one unit of supply of an item, one unit of demand, or both. The objective is to determine a minimum cost capacitated vehicle route for transporting the items in such a way that all demands are satisfied. The vehicle can carry more than one item at a time. Three mathematical programming formulations of the problem are provided. Several classes of valid inequalities are derived and incorporated within abranch-and-cut algorithm, and extensive computational experiments are performed on instances adapted from TSPLIB.
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    The attractive traveling salesman problem
    (Elsevier, 2010-05-16) Erdoğan, Güneş; Cordeau, J.-F.; Laporte, G.; Industrial Engineering; ERDOĞAN, Güneş
    In the Attractive Traveling Salesman Problem the vertex set is partitioned into facility vertices and customer vertices. A maximum profit tour must be constructed on a subset of the facility vertices. Profit is computed through an attraction function: every visited facility vertex attracts a portion of the profit from the customer vertices based on the distance between the facility and customer vertices, and the attractiveness of the facility vertex. A gravity model is used for computing the profit attraction. The problem is formulated as an integer non-linear program. A linearization is proposed and strengthened through the introduction of valid inequalities, and a branch-and-cut algorithm is developed. A tabu search algorithm is also implemented. Computational results are reported.
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    Metaheuristics for the traveling salesman problem with pickups, deliveries and handling costs
    (Elsevier, 2012-05) Erdoğan, Güneş; Battarra, M.; Laporte, G.; Vigo, D.; Industrial Engineering; ERDOĞAN, Güneş
    This paper studies the Traveling Salesman Problem with Pickups, Deliveries, and Handling Costs. The subproblem of minimizing the handling cost for a fixed route is analyzed in detail. It is solved by means of an exact dynamic programming algorithm with quadratic complexity and by an approximate linear time algorithm. Three metaheuristics integrating these solution methods are developed. These are based on tabu search, iterated local search and iterated tabu search. The three heuristics are tested and compared on instances adapted from the related literature. The results show that the combination of tabu search and exact dynamic programming performs the best, but using the approximate linear time algorithm considerably decreases the CPU time at the cost of slightly worse solutions.
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    Modelling and solving an m-location, n-courier, priority-based planning problem on a network
    (Springer Nature, 2012-01) Erdoğan, Güneş; Tansel, B.; Akgün, İ.; Industrial Engineering; ERDOĞAN, Güneş
    In this paper, we study an m-location, n-courier, priority-based planning problem on a network, which we refer to as the Courier Planning Problem (CPP). The CPP arises on a daily basis in the context of planning the transportation of materials and personnel in peacetime for the Turkish Armed Forces. The main issue addressed in CPP is to transport as many of deliverables as possible from their origins to their destinations via a fleet of transportation assets (couriers) that operate at fixed routes and schedules. Priorities must be taken into account and constraints on the routes, operating schedules, and capacities of the transportation assets must be obeyed. Time windows may be specified for some or all transportation requests and must be satisfied. We study the CPP as well as its two extensions, and present integer programming formulations based on the multi-commodity flow structure. The formulations are tested on real world-based data and display satisfactory computational performance. Our main contributions are to develop an effective formulation scheme for a complicated large-scale real world problem and to demonstrate that such problems are solvable via commercial general purpose solvers through meticulous modelling.
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    The traveling salesman problem with pickups, deliveries, and handling costs
    (Informs, 2010-08) Battarra, M.; Erdoğan, Güneş; Laporte, G.; Vigo, D.; Industrial Engineering; ERDOĞAN, Güneş
    This paper introduces a new variant of the one-to-many-to-one single vehicle pickup and delivery problems (SVPDP) that incorporates the handling cost incurred when rearranging the load at the customer locations. The simultaneous optimization of routing and handling costs is difficult, and the resulting loading patterns are hard to implement in practice. However, this option makes economical sense in contexts where the routing cost dominates the handling cost. We have proposed some simplified policies applicable to such contexts. The first is a two-phase heuristic in which the tour having minimum routing cost is initially determined by optimally solving an SVPDP, and the optimal handling policy is then determined for that tour. In addition, branch-and-cutalgorithms based on integer linear programming formulations are proposed, in which routing and handling decisions are simultaneously optimized, but the handling decisions are restricted to three simplified policies. The formulations are strengthened by means of problem specific valid inequalities. The proposed methods have been extensively tested on instances involving up to 25 customers and hundreds of items. Our results show the impact of the handling aspect on the customer sequencing and indicate that the simplified handling policies favorably compare with the optimal one.
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    ArticlePublicationOpen Access
    Computational comparison of five maximal covering models for locating ambulances
    (Wiley, 2009-01) Erkut, Erhan; Ingolfsson, A.; Sim, T.; Erdoğan, Güneş; Business Administration; Industrial Engineering; ERKUT, Erhan; ERDOĞAN, Güneş
    This article categorizes existing maximum coverage optimization models for locatingambulances based on whether the models incorporate uncertainty about (1) ambulanceavailability and (2) response times. Data from Edmonton, Alberta, Canada are used to test five different models, using the approximate hypercube model to compare solution quality between models. The basic maximum covering model, which ignores these two sources of uncertainty, generates solutions that perform far worse than those generated by more sophisticated models. For a specified number of ambulances, a model that incorporates both sources of uncertainty generates a configuration that covers up to 26% more of the demand than the configuration produced by the basic model.