The two-stage assembly flowshop scheduling problem is addressed with the objective of minimizing total tardiness. An insertion algorithm, a genetic algorithm, and a hybrid of the insertion and genetic algorithms, are developed for the problem. Conducted computational experiments reveal that the hybrid algorithm significantly outperforms the genetic algorithm while the best performing algorithm ...

In this paper a new metaheuristic method is proposed to solve the classical permutation flowshop scheduling problem with the objective of minimizing sum of completion times. The representative neighbourhood combines the stochastic sampling method mainly used in Simulated Annealing and the best descent method elaborated in Tabu Search and integrates them naturally into a single method. The metho...

The paper considers the problem of preemptive scheduling in a two-stage flowshop with parallel unrelated machines at the first stage and a single machine at the second stage. At the first stage, jobs use some additional renewable resources which are available in limited quantities. The resource requirements are of 0-1 type. The objective is minimization of the makespan. The problem is NP-hard. ...

Flowshop scheduling deals with the sequencing of a set of jobs that visit a set of machines in the same order. A tabu search procedure is proposed for the flowshop scheduling problem with the makespan minimization criterion. Different from other tabu search procedures, the neighborhood of a solution is generated using a combination of three different exchange mechanisms. This has resulted in a ...

This paper deals with a bi-objective hybrid no-wait flowshop scheduling problem minimizing the makespan and total weighted tardiness, in which we consider transportation times between stages. Obtaining an optimal solution for this type of complex, large-sized problem in reasonable computational time by using traditional approaches and optimization tools is extremely difficult. This paper presen...

In the last decades, availability constraint as well learning and deteriorating effects were introduced into production scheduling theory to simulate real-world case studies overcome limitation of classical models. To best our knowledge, this paper is first in literature address permutation flowshop problem (PFSP) with flexible maintenance under deterioration minimize makespan. Firstly, we PFSP...

In this paper, we are discussing a research project aiming to optimize the scheduling of production orders within real application in packaging field. As first approach, model problem as an extended version hybrid and flexible flowshop with precedence constraints, parallel machines, sequence-dependent setups. The optimization objective considered is minimization total tardiness. To tackle probl...

In this paper, the problem of determining the best schedule for a set of projects has been modeled in the form of a generalized tardiness flowshop (GTF) problem. We develop a set of heuristic algorithms for minimizing the total tardiness of jobs in a GTF problem. In the generalized version of tardiness flowshop problems, a job is considered to be a collection of operations and there is a due da...

An implementation of a genetic algorithm for the n/m/P/Cmax sequencing problem is presented, and two performance enhancements hybridisation with a local search algorithm, and a `string fridge` are evaluated. This implementation is then extended to allow the genetic algorithm to optimise the placement of additional processing units to enhance productivity, and to meet order deadlines. Finally, p...

This paper presents an MILP model for the permutation flowshop wherein the setup times are both separable from the job processing times and independent of a job’s position in the processing sequence. Two experiments were conducted to estimate the computer times necessary to solve problems with up to 9 machines and 15 jobs, and to then compare these solution time requirements to those required ...