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 ...

Ant colony optimization (ACO) is a meta-heuristic proposed to derive approximate solutions for computationally hard problems by emulating the natural behaviors of ants. In the literature, several successful applications have been reported for graph-based optimization problems, such as vehicle routing problems and traveling salesman problems. In this paper, we propose an application of the ACO t...

The m-machine no-wait flowshop scheduling problem, with the objective of minimizing total completion time subject to the constraint that makespan has to be less than or equal to a certain value, is addressed in this paper. First, an algorithm is proposed to find an upper bound on the makespan in case the upper bound is not given or unknown. Given the upper bound on makespan, a proposed algorith...

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...

We study the directed minimum latency problem: given an n-vertex asymmetric metric (V, d) with a root vertex r ∈ V , find a spanning path originating at r that minimizes the sum of latencies at all vertices (the latency of any vertex v ∈ V is the distance from r to v along the path). This problem has been well-studied on symmetric metrics, and the best known approximation guarantee is 3.59 [3]....

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 ...

We present an in-depth study of the simulated annealing approach to the scheduling of serial multiproduct batch processes under the assumption of a permutation schedule. Four versions of the simulated annealing algorithm are studied based on two move acceptance criteria, the Metropolis algorithm and the Glauber algorithm, and two annealing schedules, the exponential schedule and the Aarts and v...