In this paper, we are interested in the modeling and the resolution of the dynamic and discrete berth allocation problem which is noted DDBAP. To resolve this problem, we propose a heuristic approach of optimization which combines two concepts: agent and heuristics. This approach is based on the use of the multi-agent negotiation, the contract net protocol, and a set of heuristics such as the W...

In this work we study a flowshop scheduling problem in which jobs are not allowed to wait in-between machines, a situation commonly referred to as no-wait. The concerned criterion is to minimize a weighted sum of makespan and maximum lateness. A dominance relation for the case of three-machine is presented and evaluated by experimental designs. Several heuristics and local search methods are pr...

This paper proposes an Iterated Local Search (ILS) procedure and an Iterated Greedy (IG) algorithm, which are both combined with a variable neighbourhood search (VNS), for dealing with the flow shop problem with blocking, in order to minimize the total tardiness of jobs. The structure of both algorithms is very similar, but they differ in the way that the search is diversified in the space of s...

As multi-factory production models are more widespread in modern manufacturing systems, a distributed blocking flowshop scheduling problem (DBFSP) is studied which no buffer between adjacent machines and setup time constraints considered. To address the above problem, mixed integer linear programming (MILP) model first constructed, its correctness verified. Then, an iterated greedy-algorithm-bl...

In the context of Scheduling under uncertainty, Partial Order Schedules (POS) provide a convenient way to build flexible solutions. A POS is obtained from a Project Graph by adding precedence constraints so that no resource conflict can arise, for any possible assignment of the activity durations. In this paper, we use a simulation approach to evaluate the expected makespan of a number of POSs,...

current research addresses finding robust and stable schedule for the flexible job shop problem under machine breakdown. we have used simulation to investigate the effect of machine breakdown. two-stage of metaheuristic algorithm is developed to generate robust and stable schedule and is integrated with simulation algorithm. because makespan is primitive objective of every scheduling problem, i...

This paper focuses on the flowshop scheduling problem with sequence dependent setup times (FSSP-SDST), which has been an investigated object for decades as one of the most popular scheduling problems in manufacturing systems. A novel hybrid local search algorithm called HLS is presented to solve the flowshop scheduling problem with sequence dependent setup times with the criterion of minimizing...

Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. A Variable Neighborhood Genetic Algorithm (VNGA) is proposed for the problem with makespan criterion, consisting of a combination of the variable neighborhood search (VNS) and genetic algorithm (GA). Variable ne...

In traditional scheduling problems, the processing time for the given job is assumed to be a constant regardless of whether the job is scheduled earlier or later. However, the phenomenon named ‘‘learning effect’’ has extensively been studied recently, in which job processing times decline as workers gain more experience. This paper discusses a bi-criteria scheduling problem in anm-machine permu...

This paper addresses the stable scheduling of multi-objective problem in flexible job shop scheduling with random machine breakdown. Recently, numerous studies are conducted about robust scheduling; however, implementing a scheme which prevents a tremendous change between scheduling and after machine breakdown (preschedule and realized schedule, respectively) can be critical for utilizing avail...