Production planning optimization with fuzzy analytic hierarchy process and genetic algorithm

Abstract

Proper production planning is essential for improving productivity and lowering resource (material, energy, employees) related costs in the highly competitive business world. Dealing with the challenges of asymmetric setup times—where the time required to switch between manufacturing different products varies —makes this task much more difficult. Conventional planning techniques frequently ignore these articulations and produce sub-optimal schedules. This paper proposes a novel approach to tackle the following challenge: optimizing production planning using the Fuzzy Analytic Hierarchy Process (FAHP) with asymmetric setup times and Genetic Algorithm (GA). The proposed methodology involves a step-by-step process. The first stage defines key objectives: makespan, total waste cost, and maximum weighted tardiness. Decision-makers compare the relative importance of each criterion within its hierarchy level using fuzzy numbers. The consistency of these comparisons is assessed using fuzzy consistency ratio computations. At the same time, the overall priority weights for each production planning alternative are determined by summing fuzzy judgments across the hierarchy. In the second stage, the production plan is optimized using GA, considering sequence and lot size variables and asymmetric setup times, by applying the computed weights. The comparisons are performed using the proposed approach with the optimum solution.

Keywords

• Fuzzy analytic hierarchy process (FAHP)
• multi-criteria decision-making
• sequencing
• metaheuristics
• sequence-dependent setup times

Bulanık analitik hiyerarşi prosesi ve genetik algoritma ile üretim planlama optimizasyonu

Abstract

Rekabetin yoğun olduğu iş dünyasında, üretim planlamasının doğru bir şekilde yapılması, verimliliği artırmak ve kaynak (malzeme, enerji, çalışanlar) ile ilgili maliyetleri düşürmek için önemlidir. Farklı ürünler arasında geçiş sürelerinin değişiklik gösterdiği asimetrik kurulum süreleri ile başa çıkmak, bu görevi çok daha zorlaştırır. Geleneksel planlama teknikleri genellikle bu nüansları göz ardı eder ve optimal olmayan çizelgeler üretir. Bu makale, asimetrik kurulum süreleri ve Genetik Algoritma (GA) ile Bulanık Analitik Hiyerarşi Prosesi (B-AHP) kullanarak üretim planlamasını optimize etmeye yönelik yeni bir yaklaşım önermektedir. BAHS, belirsizlik ve bulanıklığı kapsayan bulanık mantığın gücünü, Analitik Hiyerarşi Prosesi’nin (AHP) yapılandırılmış hiyerarşisiyle birleştirir. Önerilen metodoloji, adım adım bir süreç içerir. İlk aşama, temel hedefleri tanımlar: iş bitirme süresi, toplam atık maliyeti ve maksimum ağırlıklı gecikme. İlk aşamada karar vericiler, her kriterin kendi hiyerarşi seviyesindeki göreceli önemini bulanık sayılar kullanarak karşılaştırır. Bu karşılaştırmaların tutarlılığı, bulanık tutarlılık oranı hesaplamaları ile değerlendirilir. Aynı zamanda, her üretim planlama alternatifi için genel öncelik ağırlıkları, hiyerarşi boyunca bulanık yargıların toplamı alınarak belirlenir. İkinci aşamada, hesaplanan ağırlıklar kullanılarak, asimetrik kurulum süreleri ile sıralama ve lot büyüklüğü değişkenlerini dikkate alarak üretim planı GA ile optimize edilir. Optimum çözüm ile önerilen yaklaşım kullanılarak karşılaştırmalar gerçekleştirilir.

Keywords

• Bulanık mantık
• üretim planlama
• analitik hiyerarşi prosesi
• metasezgisel
• genetik algoritma
• çok kriterli karar verme

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