Browsing by Subject "Near-optimal solutions"
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Item Open Access Dynamic lot sizing with multiple suppliers, backlogging and quantity discounts(Elsevier Ltd, 2017) Ghaniabadi, M.; Mazinani, A.This paper studies the dynamic lot sizing problem with supplier selection, backlogging and quantity discounts. Two known discount types are considered separately, incremental and all-units quantity discounts. Mixed integer linear programming (MILP) formulations are presented for each case and solved using a commercial optimization software. In order to timely solve the problem, a recursive formulation and its efficient implementation are introduced for each case which result in an optimal and a near optimal solution for incremental and all-units quantity discount cases, respectively. Finally, the execution times of the MILP models and forward dynamic programming models obtained from the recursive formulations are presented and compared. The results demonstrate the efficiency of the dynamic programming models, as they can solve even large-sized instances quite timely. © 2017Item Open Access A joint production and transportation planning problem with heterogeneous vehicles(2014) Toptal, A.; Koc, U.; Sabuncuoglu, I.We consider a manufacturer's planning problem to schedule order production and transportation to respective destinations. The manufacturer in this setting can use two vehicle types for outbound shipments. The first type is available in unlimited numbers. The availability of the second type, which is less expensive, changes over time. Motivated by some industry practices, we present formulations for three different solution approaches: the myopic solution, the hierarchical solution and the coordinated solution. These approaches vary in how the underlying production and transportation subproblems are solved, that is, sequentially versus jointly or heuristically versus optimally. We provide intractability proofs or polynomial-time exact solution procedures for the sub-problems and their special cases. We also compare the three solution approaches over a numerical study to quantify the savings from integration and explicit consideration of transportation availabilities. Our analytical and numerical results set a foundation and a need for a heuristic to solve the integrated problem. We thus propose a tabu search heuristic, which quickly generates near-optimal solutions.Item Open Access Joint routing, gateway selection, scheduling and power management optimization in wireless mesh networks(Institute of Industrial Engineers, 2012-05) Uzunlar Onur; Gökbayrak, Kağan; Yıldırım, E. A.The third generation (3G) wireless communications technology delivers user traffic in a single step to the wired network via base station; therefore it requires all base stations to be connected to the wired network. On the other hand, in the fourth generation (4G) communication systems, it is planned to have the base stations set up so that they can deliver each other's traffic to a small number of base stations equipped with wired connections. In order to improve system resiliency against failures, a mesh structure is preferred. The most important issue in Wireless Mesh Networks (WMN) is that the signals that are simultaneously transmitted on the same frequency channel can interfere with each other to become incomprehensible at the receiver end. It is possible to operate the links at different times or at different frequencies, but this also lowers capacity usage. In this paper, we tackle the planning problems of WMN, using 802.16 (Wi-MAX) protocol, such as deploying a given number of gateway nodes along with operational problems such as routing, management of power used by nodes and scheduling while maximizing the minimum service level provided. In order to be able to apply our results to real systems, we work with optimization models based on realistic assumptions such as physical interference and single path routing. We propose heuristic methods to obtain optimal or near optimal solutions in reasonable time. The models are applied to some cities in Istanbul and Ankara provinces.Item Open Access Multi-population parallel genetic algorithm using a new genetic representation for the euclidean traveling salesman problem(İstanbul Technical University, 2005) Kapanoğlu, M.; Koç, İ. O.; Kara, İ.; Aktürk, Mehmet SelimThis paper introduces a multi-population genetic algorithm (M-PPGA) using a new genetic representation, the kth-nearest neighbor representation, for Euclidean Traveling Salesman Problems. The proposed M-PPGA runs M greedy genetic algorithms on M separate populations, each with two new operators, intersection repairing and cheapest insert. The M-PPGA finds optimal or near optimal solutions by using a novel communication operator among individually converged populations. The algorithm generates high quality building blocks within each population; then, combines these blocks to build the optimal or near optimal solutions by means of the communication operator. The proposed M-PPGA outperforms the GAs that we know of as competitive with respect to running times and solution quality, over the considered test problems including the Turkey81.