This paper presents an effective stochastic algorithm that embeds a large neighborhood decomposition technique into variable search for solving the permutation flow-shop scheduling problem. The first constructs as seed using recursive application of extended two-machine In this method, jobs are recursively decomposed two separate groups, and, each group, optimal is calculated based on Then over...

Flow Shop Scheduling Problem (FSSP) has significant application in the industry, and therefore it been extensively addressed literature using different optimization techniques. Current research investigates Permutation (PFSSP) to minimize makespan Hybrid Evolution Strategy (HES SA ). Initially, ...

In this paper a Genetic Algorithm (GA) approach is presented to solve the N-Jobs M-Machines Permutation Flow-Shop Scheduling Problem (PFSP) with Break-down times. In comparison with other methods that start with a solution obtained with the Johnson’s Algorithm (or another greedy approach), the presented GA method starts with randomly generated solutions and within 100 iterations is able to obta...

We consider the ow-shop scheduling problem. The objective is to schedule the jobs on the machines so that we minimize the time by which all jobs are completed. We studied and implemented diierent versions of the algorithm of Sevast'yanov based on linear programming to solve this problem. Using CPLEX, we did computational tests with random instances having up to 1000 jobs and 100 machines. If th...

This paper deals with a permutation flow-shop scheduling problem with finite intermediate storage (PFSFIS) between successive machines so as to minimize makespan. In such a problem the intermediate storage capacity constraints are considered besides the machine-related constraints usually discussed in the general permutation flow-shop. This feature adds extra difficulties to the scheduling prob...

Focusing on the generation mechanism of random permutation solutions, this paper investigates the application of the Simulated Annealing (SA) algorithm to the combinatorial optimisation problems with permutation property. Six types of perturbation scheme for generating random permutation solutions are introduced. They are proved to satisfy the asymptotical convergence requirements. The results ...

In this paper, we propose a general agent-based distributed framework where each agent is implementing a different metaheuristic/local search combination. Moreover, an agent continuously adapts itself during the search process using a direct cooperation protocol based on reinforcement learning and pattern matching. Good patterns that make up improving solutions are identified and shared by the ...