Çok amaçlı tesis yerleşim problemi için yeni bir melez sezgisel algoritma

Bu makalede, Çok Amaçlı Tesis Yerleşim Probleminin (ÇATYP) çözümü için, tabu listesi ile desteklenmiş, Tavlama Benzetimi’ne (TB) dayalı yeni bir melez sezgisel algoritma önerilmektedir. TB’ne tabu listesinin eklenmesiyle oluşturulan yeni melez sezgisel algoritmanın en önemli avantajı, TB’nin olasılıklı yapısı korunurken, aynı zamanda kısa dönemli hafıza (tabu listesi) ile daha önce üretilen komşu çözümlerin tekrar üretilmesinin engellenmesidir. Yeni melez sezgisel algoritmanın amacı, ÇATYP’nin etkin çözümler kümesini (pareto optimal set) oluşturan çözümleri kısa zaman içinde bulmaktır. Yeni melez sezgisel algoritmanın etkinliği 8 bölüm ve 4 amaçtan oluşan bir örnek problem üzerinde gösterilmiştir. Algoritma ile önceden belirlenmiş ağırlıklar için en iyi yerleşim planı ile aynı zamanda problemin etkin çözümlerinin oluşturduğu pareto çözümler kümesi bulunmuştur.

A new hybrid heuristic algorithm for the multi objective facility layout problem

In this paper, we propose a new hybrid meta-heuristic algorithm based on simulated annealing supplemented with tabu list for the Multi Objective Facility Layout Problem (MOFLP). It is a SA approach supplemented with a tabu list. The main advantage of this approach is that a short term memory provided by the tabu list can be used to avoid solution re-visits while preserving the stochastic nature of the SA method. The goal of the new hybrid heuristic algorithm is to find the solutions forming the set of efficient solutions (pareto optimal set) of the MOFLP’s in a relatively short time. The hybrid meta-heuristic is illustrated with a practical example of plant with 8 departments and 4 objectives. An efficient set of layouts corresponding to pre-determined weights are obtained. And also the set of efficient pareto-optimal solutions of the problem are determined.

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