Ramazan Şahin

A simulated annealing heuristic for the dynamic layout problem with budget constraint

Facility layout problem has been extensively studied in the literature because the total material handling cost can be a significant portion in the operational costs for a company and in the manufacturing cost of a product. Todays severe global competition, rapid changes in technology and shortening life cycle of products force companies to evaluate and modify their facility layout in a periodic fashion. This type of layout problems is categorized as the dynamic facility layout problem (DFLP). As a realistic dimension of the problem, one has to consider also the limited budget to cover the cost of changing the layout. In this study, we propose a simulated annealing heuristic for the DFLP with budget constraint, and show the effectiveness of this heuristic on a set of numerical experiments.

A simulated annealing algorithm for solving the bi-objective facility layout problem

In this article, a bi-objective facility layout problem (BOFLP) is considered by combining the objectives of minimization of the total material handling cost (quantitative) and the maximization of total closeness rating scores (qualitative), with the predetermined weights are assigned to the respective objectives. A simulated annealing (SA) algorithm is proposed to solve the BOFLP, as well as a comparison of SA with the previous works is provided. It is shown that the SA algorithm works better than the previous works; thus proving the fact that the proposed SA algorithm is an efficient method for solving BOFLP.

A new hybrid tabu-simulated annealing heuristic for the dynamic facility layout problem

In todays market conditions of increasing global competition, rapid changes in technology and shorter life cycle of product, it is required to evaluate the facility layout as the dynamic facility layout problem (DFLP). The objective of the DFLP is to determine layouts for each period in the planning horizon such that the sum of material handling and rearrangement costs are minimised. In the literature several researchers proposed new algorithms and models to solve the problem. The purpose of this research is to present a new hybrid heuristic based on the simulated annealing (SA) approach supplemented with a tabu list for the DFLP. We call this heuristic TABUSA. The efficiency of the TABUSA algorithm is analysed by solving the problems in a well known data set from the literature. We have also solved the same problems by using a pure SA algorithm, and a pure tabu search (TS) algorithm for comparison purposes. The results show the effectiveness of the TABUSA algorithm.

Modified migrating birds optimization algorithm for closed loop layout with exact distances in flexible manufacturing systems

The paper modifies MBO algorithm using GA operators.The paper considers exact distances in layout evaluation.Taguchi method is used to calibrate the parameters of the algorithm.The modified MBO performs better than previous algorithms and also exact methods. This paper addresses a new meta-heuristic algorithm to solve a closed loop layout problem. The proposed algorithm applies a modified version of the recently invented migrating birds optimization method. The computational experiments show that in most of the benchmark problems the results obtained from the proposed migrating birds optimization method is better than those obtained by other methods which are published in the literature.

A comprehensive mathematical model for dynamic cellular manufacturing system design and Linear Programming embedded hybrid solution techniques

A comprehensive linear mathematical model for dynamic cellular manufacturing system design.A Linear Programming embedded Simulated Annealing technique.A Linear Programming embedded Genetic Algorithm technique.Samples taken from the literature were solved and compared with previous results.A lower bound mathematical model is also proposed. Considering the ever changing market conditions, it is essential to design responsive and flexible manufacturing systems. This study addresses the multi-period Dynamic Cellular Manufacturing System (DCMS) design problem and introduces a new mathematical model. The objective function of the mathematical model considers inter-cell and intra-cell material handling, machine purchasing, layout reconfiguration, variable and constant machine costs. Machine duplication, machine capacities, operation sequences, alternative processing routes of the products, varying demands of products and lot splitting are among the most important issues addressed by the mathematical model. It makes decisions on many system related issues, including cell formation, inter- and intra-cell layout, product routing and product flow between machines. Due to the complexity of the problem, we suggest two heuristic solution approaches that combine Simulated Annealing (SA) with Linear Programming and Genetic Algorithm (GA) with Linear Programming. The developed approaches were tested using a data set from the literature. In addition, randomly generated test problems were also used to investigate the performance of the hybrid heuristic approaches. A problem specific lower bound mathematical model was also proposed to observe the solution quality of the developed approaches. The suggested approaches outperformed the previous study in terms of both computational time and the solution quality by reducing the overall system cost.

ÇOK AMAÇLI TESİS YERLEŞİM PROBLEMİ İÇİN YENİ BİR MELEZ SEZGİSEL ALGORİTMA

Bu makalede, Cok Amacli Tesis Yerlesim Probleminin (CATYP) cozumu icin, tabu listesi ile desteklenmis,Tavlama Benzetimi’ne (TB) dayali yeni bir melez sezgisel algoritma onerilmektedir. TB’ne tabu listesinineklenmesiyle olusturulan yeni melez sezgisel algoritmanin en onemli avantaji, TB’nin olasilikli yapisi korunurken,ayni zamanda kisa donemli hafiza (tabu listesi) ile daha once uretilen komsu cozumlerin tekrar uretilmesininengellenmesidir. Yeni melez sezgisel algoritmanin amaci, CATYP’nin etkin cozumler kumesini (pareto optimalset) olusturan cozumleri kisa zaman icinde bulmaktir. Yeni melez sezgisel algoritmanin etkinligi 8 bolum ve 4amactan olusan bir ornek problem uzerinde gosterilmistir. Algoritma ile onceden belirlenmis agirliklar icin en iyiyerlesim plani ile ayni zamanda problemin etkin cozumlerinin olusturdugu pareto cozumler kumesi bulunmustur.