In this paper novel hybrid genetic algorithms for Open--Shop Scheduling Problem (OSSP) are presented. Two greedy heuristics LPT-Task and LPT-Machine are proposed for decoding chromosomes represented by permutations with repetitions. For comparison the standard permutation representation of OSSP instances is used. The algorithms apply also efficient crossover operator LOX and mutation operators ...

This paper examines how the search ability of evolutionary multi-objective optimization (EMO) algorithms can be improved by the hybridization with local search through computational experiments on multi-objective permutation flowshop scheduling problems. The task of EMO algorithms is to find a variety of nondominated solutions of multi-objective optimization problems. First we describe our mult...

This paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. First, the problem is formulated as a mixed integer linear programming model. Then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. Two experiments are carried out to evaluate th...

In recent years Cellular Manufacturing has become an effective tool for improving productivity. Attainment of full benefits of Cellular Manufacturing depends firstly on the design of the machine cells and part families, secondly on the method of operations which takes full advantage of cell properties. Inappropriate methods of loading and scheduling can even lead to the failure of the Cellular ...