Mohamed Kais Msakni

The two-machine flowshop scheduling problem with sequence-independent setup times: New lower bounding strategies

The two-machine flowshop environment with sequence-independent setup times has been intensely investigated both from theoretical and practical perspectives in the scheduling literature. Nevertheless, very scant attention has been devoted to deriving effective lower bounding strategies. In this paper, we propose new lower bounds for the total completion time minimization criterion. These bounds are based on three relaxation schemes, namely the waiting time-based relaxation scheme, the single machine-based relaxation scheme, and the Lagrangian relaxation scheme. Extensive computational study carried on instances with up to 500 jobs reveals that embedding the waiting time-based bounding strategy within the Lagrangian relaxation framework yields the best performance while requiring negligible CPU time.

Minimizing the total completion time in a two-machine flowshop problem with time delays

This article proposes to solve the problem of minimizing the total completion time in a two-machine permutation flowshop environment in which time delays between the machines are considered. For this purpose, an enumeration algorithm based on the branch-and-bound framework is developed, which includes new lower and upper bounds as well as dominance rules. The computational study shows that problems with up to 40 jobs can be solved in a reasonable amount of time.

A comprehensive annual delivery program for upstream liquefied natural gas supply chain

Developing a cost-effective annual delivery program (ADP) is a challenging task for liquefied natural gas (LNG) suppliers, especially for LNG supply chains with large number of vessels and customers. Given significant operational costs in LNG delivery operations, cost-effective ADPs can yield substantial savings, adding up to millions. Providing an extensive account of supply chain operations and contractual terms, this paper aims to consider a realistic ADP problem faced by large LNG suppliers; suggest alternative delivery options, such as split-delivery; and propose an efficient heuristic solution which outperforms commercial optimizers. The comprehensive numerical study in this research demonstrates that contrary to the common belief in practice, split-delivery may generate substantial cost reductions in LNG supply chains.

Minimizing the Total Completion Time in a Two-Machine Flowshop with Sequence-Independent Setup Times

We consider the problem of minimizing the sum of completion times in a two-machine permutation flowshop subject to setup times. We propose a new priority rule, several constructive heuristics, local search procedures, as well as an effective multiple crossover genetic algorithm. Computational experiments carried out on a large set of randomly generated instances provide evidence that a constructive heuristic based on newly derived priority rule dominates all the proposed constructive heuristics. More specifically, we show that one of our proposed constructive heuristics outperforms the best constructive heuristic in the literature in terms of both error and computational time. Furthermore, we show that one of our proposed local search-based heuristics outperforms the best local search heuristic in the literature in terms of again both error and computational time. We also show that, in terms of quality-to-CPU time ratio, the multiple crossover genetic algorithm performs consistently well.

Polynomial Lower Bounds for the Two-Machine Flowshop Problem with Sequence-Independent Setup Times

In this paper, we address the problem of two-machine flowshop scheduling problem with sequence independent setup times to minimize the total completion time. We propose five new polynomial lower bounds. Computational results based on randomly generated data show that our proposed lower bounds consistently outperform those of the literature.

Heuristic algorithms for minimizing total completion time in a two-machine flowshop with sequence-independent setup times

In this paper, we address the two-machine flowshop with sequence-independent setup times. Heuristic algorithms are proposed to find a near-optimal solution. We propose a constructive heuristic based on new priority rule, local search procedures and a genetic local search algorithm for the problem under consideration. Computational results show that local search procedures contribute to have a better results.

An Integrated Quay Crane Assignment and Scheduling Problem Using Branch-and-Price

This paper investigates the integrated quay crane assignment and scheduling problem (QCASP). The problem requires determining the assignment of quay cranes to vessels and the scheduling of operations to be performed by each quay crane. Different practical aspects of the problem are considered including non-crossing and safety margin constraints. The resulting problem is NP-complete and, therefore, requires advanced techniques to solve it. For this purpose, we propose an exact method based on a branch-and-price algorithm. Computational experiments show that the proposed method can solve large-sized problems efficiently.

A New Genetic Algorithm for Designing Cellular Manufacturing Systems with Labor and Tools Issues

This paper considers the problem of designing cellular manufacturing systems (CMS) with the presence of alternate process plans, tools and workers. The objective is to minimize the total costs of machine installation, operations, tools and workers with a number of identified practical constraints. A genetic algorithm is designed in order to efficiently solve medium and large sized problems. Preliminary numerical results show the worth of implementing the suggested procedure.

New characteristics of optimal solutions for the two-machine flowshop problem with unlimited buffers

Abstract The two-machine flowshop problem with unlimited buffers with the objective of minimising the makespan (F2||Cmax) is addressed. Johnson’s algorithm finds optimal solutions (permutations) to this problem, but are not necessarily the only optimal solutions. We show in this paper that certain jobs that we define as Critical Jobs, must occupy specific positions in any optimal sequence, not only in Johnson’s solutions. We also prove that jobs that precede a critical job cannot be exchanged with jobs that succeed it in an optimal sequence, which reduces the number of enumerations necessary to identify all optimal solutions. The findings of this research can be useful in reducing the search space for optimal enumeration algorithms such as branch-and-bound.

Exact methods for the quay crane scheduling problem when tasks are modeled at the single container level

Abstract The scheduling of quay cranes (QCs) to minimize the handling time of a berthed vessel is one of the most important operations in container terminals as it impacts the terminal’s overall productivity. In this paper, we propose two exact methods to solve the quay crane scheduling problem (QCSP) where a task is defined as handling a single container and subject to different technical constraints including QCs’ safety margin, non-crossing, initial position, and nonzero traveling time. The first method is based on two versions of a compact mixed-integer programming formulation that can solve large problem instances using a general purpose solver. The second is a combination of some constraints of the proposed mathematical model and the binary search algorithm to reduce the CPU time, and solve more efficiently large-sized problems. Unlike existing studies, the computational study demonstrates that both methods can reach optimal solutions for large-sized instances and validates their dominance compared to an exact model proposed in the literature which finds solutions only for small problems.