This paper proposes a hybridized simheuristic approach that couples greedy randomized adaptive search procedure (GRASP), Monte Carlo simulation, Pareto archived evolution strategy (PAES), and an analytic hierarchy process (AHP), in order to solve multicriteria stochastic permutation flow shop problem with processing times sequence-dependent setup times. For the decisional criteria, proposed con...

Abstract System-wide optimization of distributed manufacturing operations enables process improvement beyond the standalone and individual optimality norms. This study addresses production planning a system consisting three stages: parts (subcomponents), assembly components in Original Equipment Manufacturer (OEM) factories, final products at product manufacturer’s factory. Distributed Three St...

In this paper, we consider a flow shop scheduling problem with availability constraints (FSSPAC) for the objective of minimizing the makespan. In such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. We proposed a mixed-integer linear programming (MILP) model for this problem which can generate non-permutation schedules. Furthermor...

An uncertain version of the permutation flow-shop with unlimited buffers and the makespan as a criterion is considered. The investigated parametric uncertainty is represented by given interval-valued processing times. The maximum regret is used for the evaluation of uncertainty. Consequently, the minmax regret discrete optimization problem is solved. Due to its high complexity, two relaxations ...

This paper presents the development of an alternative method for makespan computation algorithms of a re-entrant flow shop scheduling problem using bottleneck analysis. The computation is specifically intended for the cyber manufacturing centre (CMC) which is an Internet based collaborative design and manufacturing services at Universiti Tun Hussein Onn Malaysia. The CMC processes scheduling re...

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...

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...

Factory management plays an important role in improving the productivity and quality of service in the production process. In particular, the distributed permutation flow shop scheduling problem with multiple factories is considered a priority factor in the factory automation. This study proposes a novel model of the developed distributed scheduling by supplementing the reentrant characteristic...

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 ...