No abstract

No abstract

No abstract

No abstract

Fatigue causes cracking or breakage in a material due to repeated loads; it causes the material to become unusable. Therefore, knowing the fatigue life of materials is crucial for the implementation of designs, economy and human life. Soft computing methodologies, a subset of artificial intelligence emerging to simulate human intelligence, deal with approximate models and seek solutions to complex real-life problems relying on both computational power of machines and the high accuracy of the algorithms. In this study, soft computing methods adapted for estimating/predicting the fatigue life of engineering structures and materials are investigated. For this purpose, 95 articles published between 1995 and 2020 have been examined in detail. With this review, it is aimed to reveal the efficiency of soft computing methods and contribute to their development. Recommendations have been made to draw attention to these methodologies which are expected to be used in many areas in the future.

No abstract

No abstract

a b s t r a c tThis paper presents a fuzzy extension of the disassembly line balancing problem (DLBP) with fuzzy task processing times since uncertainty is the main character of real-world disassembly systems. The processing times of tasks are formulated by triangular fuzzy membership functions. The balance measure function is modified according to fuzzy characteristics of the disassembly line. A hybrid discrete artificial bee colony algorithm is proposed to solve the problem whose performance is studied over a well-known test problem taken from open literature and over a new data set introduced in this study. Furthermore, the influence of the fuzziness on the computational complexity of HDABC is evaluated and the solution quality of the proposed algorithm is compared against discrete and traditional versions of the artificial bee colony algorithm. Computational comparisons demonstrate the superiority of the proposed algorithm.