Modified genetic algorithm for simple straight and U-shaped assembly line balancing with fuzzy processing times

Fuzzy adaptive genetic algorithm for multi-objective assembly line balancing problems

“…To find the optimal factor combination, both S/N ratio and RDI are needed to be maximized regardless of their objective function value. Summing up, a level for parameters should be selected and in this level, S/N ratio has maximum value while RDI has the minimum value in comparison with the other levels, and just in case a level of these criteria are not satisfied simultaneously, another experiment for that specific parameter should be designed [55]. Controllable factors which are selected for this portion are population size, maximum number of iteration, crossover rate, and mutation rate.…”

Integrated multi-objective process planning and flexible job shop scheduling considering precedence constraints

“…Generally, most of the setup plans satisfy the first constraint. The concept of hybrid graph theory, which transferred the indirect graph to directed graph by changing the two-way edge into one way edge, which is effectively used in setup planning, was introduced by Alavidoost, Tarimoradi, and Zarandi (2015a), Alavidoost et al (2014), Tarimoradi, Alavidoost, and Zarandi (2015), Zhang and Lin (1999), and Zhang et al (2001). Here, the tolerance relations were used as the critical constraints of setup planning (Zhang et al, 2001) applied to the tolerance decomposition, fixture design and manufacturing capability in setup planning to determine the number and sequences of setups, select the datum, machining features and operations in each setup.…”

A geometrical model for managing surface productivity of U-shaped assembly lines

“…More recent work addresses the ULB problem again but from other perspectives; e.g., Oksuz et al [18] solved the ULB problem by also considering the worker performance. Optimization methods such as genetic algorithms have also been applied in recent years for either U-SAL balancing [19] or for optimizing the design of material handling systems of lean automation lines [20].…”