in this paper, we propose an iterated greedy algorithm for solving the blocking flow shop scheduling problem with total flow time minimization objective. the steps of this algorithm are designed very efficient. for generating an initial solution, we develop an efficient constructive heuristic by modifying the best known neh algorithm. effectiveness of the proposed iterated greedy algorithm is t...

In this paper, we propose an iterated greedy algorithm for solving the blocking flow shop scheduling problem with total flow time minimization objective. The steps of this algorithm are designed very efficient. For generating an initial solution, we develop an efficient constructive heuristic by modifying the best known NEH algorithm. Effectiveness of the proposed iterated greedy algorithm is t...

this paper explores the flexile flow lines where setup times are sequence- dependent. the optimization criterion is the minimization of total weighted completion time. we propose an iterated greedy algorithm (iga) to tackle the problem. an experimental evaluation is conducted to evaluate the proposed algorithm and, then, the obtained results of iga are compared against those of some other exist...

This paper explores the flexile flow lines where setup times are sequence- dependent. The optimization criterion is the minimization of total weighted completion time. We propose an iterated greedy algorithm (IGA) to tackle the problem. An experimental evaluation is conducted to evaluate the proposed algorithm and, then, the obtained results of IGA are compared against those of some other exist...

In this paper, we propose an iterated greedy algorithm for solving the blocking flow shop scheduling problem with total flow time minimization objective. The steps of this algorithm are designed very efficient. For generating an initial solution, we develop an efficient constructive heuristic by modifying the best known NEH algorithm. Effectiveness of the proposed iterated greedy algorithm is t...

Wemotivate, derive and implement a multilevel approach to the graph colouring problem. The resulting algorithm progressively coarsens the problem, initialises a colouring and then employs either Culberson’s iterated greedy algorithm or tabu search to refine the solution on each of the coarsened problems in reverse order. Tests on a large suite of problem instances indicate that for low-density ...