This paper will relate initially to the scheduling characteristics of flexible manufacturing systems, and more specifically, the scheduling problems in flowshop and hybrid flowshop type systems representing interesting structures for the modeling of several problems resulting from the industrial world. Subsequently, we will focus our attention on the principal methods for solving scheduling problems, while presenting in the following the main published works for the aforementioned systems. Lastly, a comparative analysis will be carried out to highlight the fundamental ideas leading to the adoption of an effective approach capable of producing an optimal solution in a reasonable calculation time.
Most of the prior investigations related to production scheduling problems have solely focused on the optimization of an individual criterion under a single constraint; nevertheless, this is most of the time out of true in a real situation. This paper deals with multi machines permutation flow shop scheduling with limited buffers capacity and different release dates of jobs, where the performance is measured by the minimization of the weighted sum of maximum tardiness and makespan. To tackle this NP-hard problem, we present a mixed-integer linear programming model (MILP). Thereafter, using CPLEX software, we generate a set of tests in an endeavor to examine formulation for dissimilar size problems in terms of optimality solution and computational CPU time complexity. Experiment results show that overall the proposed model is computationally avaricious to solve the considering problem.
This paper suggests two evolutionary optimization approaches for solving the blocking flow shop scheduling problem with the maximum completion time (makespan) criterion, namely the genetic algorithm (GA) and the simulated annealing genetic algorithms (SAGA) that combines the simulated annealing (SA) with the (GA), respectively. The considered problem and the proposed algorithms have some parameters to be adjusted through a design of experiments with exorbitant runs. In fact, a Taguchi method is presented to study the parameterization problem empirically. The performance of the proposed algorithms is evaluated by applying it to Taillard’s well-known benchmark problem, the experiment results show that the SA combined with GA method is advanced to the GA and to the compared algorithms proposed in the literature in minimizing makespan criterion. Ultimately, new known upper bounds for Taillard’s instances are reported for this problem, which can be used thereafter as a basis of benchmark in eventual investigations.
Different approaches to solve location problems in transport and logistics have been developed in the literature. This article introduces a new approach using the concept of persistent homology which has been proved to be an efficient method in topological data analysis; and has been served as an alternative new tool in many and various research areas such as image processing, material science and biological systems. Precisely, inspired by the notions of the first homology groups and the persistent homology which mainly describe the behaviour of connectivity relation between elements during a filtration of specific topological spaces; we develop a new method and approach for the treatment of facility location–network design problems.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.