Nozha Zribi

Assignment and Scheduling in Flexible Job-Shops by Hierarchical Optimization

In this paper, we propose a new hierarchical method for the flexible job-shop scheduling problem (FJSP). This approach is mainly adapted to a job-shop problem (JSP) with high flexibility and is based on the decomposition of the problem in an assignment subproblem and a sequencing subproblem. For the first subproblem, we propose two methods: the first one is based successively on a heuristic approach and a local search; the second one, however, is based on a branch-and-bound algorithm. The quality of the assignment is evaluated by a lower bound. For the second subproblem we apply a hybrid genetic algorithm to deal with the sequencing problem. Computational tests are finally presented.

Hybrid genetic algorithm for the flexible job-shop problem under maintenance constraints

Most scheduling literature assumes that machines are available at all times. In this paper, we study the flexible Job-shop scheduling problem where the machine maintenance has to be performed within certain intervals and hence the machine becomes unavailable during the maintenance periods. We propose an assignment technique based successively on the use of different priority rules and a local search procedure. An adequate criteria is developed to evaluate the quality of the assignment. The sequencing problem is solved by a hybrid genetic algorithm which takes into account the constraint of availability periods.

Itinerary optimisation approach inside hypermarkets

Computing the shortest path to pick up items existing in a shopping list is a principle function for an indoor intelligent navigation system dedicated to customers inside hypermarkets. In this paper, we introduce an optimization approach based on tabu search to compute the route visiting all items in the list. We consider that the list contains some promotional items with time windows. Furthermore, we introduce two Android mobile applications using the itinerary optimisation algorithm.

Total Tardiness in a Flexible Job-shop

We propose in this paper different approaches for the flexible job shop scheduling problem. The chosen criterion is the total tardiness due to the importance of respecting the due dates in production process and in the whole supply chain. The first approach is based on the decomposition of the problem in an assignment problem and a sequencing problem. The first part is ensured by an assignment technique based on a heuristic approach and the definition of an intermediary criteria. The second part consists in applying a genetic algorithm to deal with the sequencing problem. The second approach is rather an integrated one based on genetic algorithm and the generalization of a coding used for the classic job-shop

Itinerary optimisation approach with time windows inside hypermarkets

Computing the shortest path to pick up items existing in a shopping list is a principle function for an indoor intelligent navigation system dedicated to customers inside hypermarkets. In this paper, we introduce an optimization approach based on tabu search to compute the route visiting all items in the list. We consider that the list contains some promotional items with time windows.

Hierarchical Optimization for the Flexible Job Shop Scheduling Problem

Abstract In this paper we propose a new approach for the flexible job shop scheduling problem. This approach is based on the decomposition of the problem in an assignrnent problem and a sequencing probleln. The first part is ensured by an assignment technique based successively on a heuristic approach and a local search. The second part consists in applying a genetic algorithm to deal with the sequencing problem. Finally a comparison with different existing results in the literature is carried out.