Browsing by Author "Dengiz, B."

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Open Access
A local search heuristic with self-tuning parameter for permutation flow-shop scheduling problem
(IEEE, 2009) Dengiz, B.; Alabaş-Uslu, Ç.; Sabuncuoğlu, İhsan
In this paper, a new local search metaheuristic is proposed for the permutation flow-shop scheduling problem. In general, metaheuristics are widely used to solve this problem due to its NP-completeness. Although these heuristics are quite effective to solve the problem, they suffer from the need to optimize parameters. The proposed heuristic, named STLS, has a single self-tuning parameter which is calculated and updated dynamically based on both the response surface information of the problem field and the performance measure of the method throughout the search process. Especially, application simplicity of the algorithm is attractive for the users. Results of the experimental study show that STLS generates high quality solutions and outperforms the basic tabu search, simulated annealing, and record-to-record travel algorithms which are well-known local search based metaheuristics.
Open Access
Traveling repairmen problem: A biogeography-based optimization
(Springer Cham, 2022-07-14) Öder Uzun, G.; Dengiz, B.; Kara, İ.; Karasan, Oya Ekin; Xu, Jiuping; Altıparmak, Fulya; Hassan, Mohamed Hag Ali; Márquez, Fausto Pedro García; Hajiyev, Asaf
Traveling Repairman Problem (TRP), which is also known by names cumulative traveling salesman problem, the deliveryman prob lem and the minimum latency problem, is a special variant of Traveling Salesman Problem (TSP). In contrast to the minimization of completion time objective of TSP, the desired objective of TRP is to minimize the cumulative latency (waiting time or delay time) of all customers. In this paper, a generalized version of TRP with multi depots and time windows, namely Multi Depot Traveling Repairman Problem with Time Windows (MDTRPTW) is considered. A group of homogeneous repairmen initi ate and finish their visit tours at multiple depots. Each customer must be visited exactly by one repairman within their provided earliest end latest times. Being a challenging Nondeterministic Polynomial-hard (NP hard) optimization problem, exact solution approaches are not expected to scale to realistic dimensions of MDTRPTW. Thus, we propose a biogeography-based optimization algorithm (BBOA) as a metaheuristic approach to solve large size MDTRPTW problems. The proposed meta heuristic is analyzed in terms of solution quality, coefficient of variation as well as computation time by solving some test problems adapted from the related literature. The efficacy of the proposed solution methodology is demonstrated by solving instances with 288 customers within seconds.