Browsing by Author "Battarra, M."

Now showing 1 - 3 of 3

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Disaster preparedness using risk-assessment methods from earthquake engineering
(Elsevier, 2018-09-01) Battarra, M.; Koyuncu, Burcu Balçık; Xu, H.; Industrial Engineering; KOYUNCU, Burcu Balçık
Analyzing the uncertainties associated with disaster occurrences is critical to make effective disaster preparedness plans. In this study, we focus on pre-positioning emergency supplies for earthquake preparedness. We present a new method to compute earthquake likelihood and the number of the affected people. Our approach utilizes forecasting methods from the earthquake engineering literature, and avoids using probabilistic scenarios to represent the uncertainties related to earthquake occurrences. We validate the proposed technique by using historical earthquake data from Turkey, a country under significant earthquake risk. We also present a case study that illustrates the implementation of our method to solve the inventory allocation problem of the Turkish Red Crescent
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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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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.