This paper deals with a flowshop scheduling problem with a special blocking RCb (Release when Completing Blocking). In some industrial environments, such flexible production systems can be encountered. Genetic algorithms are good methods to solve these problems. A method is proposed to further improve solutions already found by genetic algorithms. It consists in marking out recurrent genes asso...

Over the last decade many metaheuristics have been applied to the flowshop scheduling problem, ranging from Simulated Annealing or Tabu Search to complex hybrid techniques. Some of these methods provide excellent effectiveness and efficiency at the expense of being utterly complicated. In fact, several published methods require substantial implementation efforts, exploit problem specific speed-...

We are interested in this paper in solving a multiobjective hybrid flowshop scheduling problem (HFS). The problem has different parameters and constraints such as release dates, due dates and sequence dependent setup times. Two different objectives should be optimized at once: the makespan and the total tardiness to be minimized. To solve the problem, we have developed two versions of a new dec...

This work presents a development of a capable-to-promise system for companies that operate under the hybrid make-to-order and maketo-stock strategy in a lot-sizing and flowshop environment. Proposed system simultaneously considers planning and scheduling processes in order to achieve the optimality. Optimisation engine is based on an advanced evolutionary algorithm. Information available in ERP...

The emergence of new hybrid and heterogenous multi-GPUs multiCPUs large scale platforms offers new opportunities and poses new challenges when solving difficult optimization problems. This paper targets irregular tree search algorithms in which workload is unpredictable. We propose an adaptive distributed approach allowing to distribute the load dynamically at runtime while taking into account ...

This paper explores a specific combinatorial problem relating to re-entrant jobs on parallel primary machines, with a remote server machine. A middle operation is required by each job on the server before it returns to its primary processing machine. The problem is inspired by the logistics of a semi-automated micro-biology laboratory. The testing programme in the laboratory corresponds roughly...

In this paper, we propose three new metaheuristic implementations to address the problem of minimizing the makespan in a hybrid flexible flowshop with sequence-dependent setup times. The first metaheuristic is a genetic algorithm (GA) embedding two new crossover operators, and the second is an ant colony optimization (ACO) algorithm which incorporates a transition rule featuring lookahead infor...

In this paper, we examine the use of biased neighborhood structures for local search in multiobjective memetic algorithms. Under a biased neighborhood structure, each neighbor of the current solution has a different probability to be sampled in local search. In standard local search, all neighbors of the current solution usually have the same probability because they are randomly sampled. On th...

This paper introduces an automated approach called OSCAR that combines algorithm portfolios and online algorithm selection. The goal of algorithm portfolios is to construct a subset of algorithms with diverse problem solving capabilities. The portfolio is then used to select algorithms from for solving a particular (set of) instance(s). Traditionally, algorithm selection is usually performed in...

In this paper, a general multi-level decomposition based framework has been proposed for integration of planning and scheduling in a multi-site, multi-product plant, with applications to paper manufacturing. The problem involves complex issues relating to large-scale production in a hybrid flowshop configuration, decisions relating to minimizing trim losses, while maintaining on-time delivery o...