Ehsan Teymourian

Minimising makespan in the two-stage assembly hybrid flow shop scheduling problem using artificial immune systems

Two-stage hybrid flow shop (HFS) scheduling problem followed by single assembly machine is addressed in this paper. To produce the final product, parts need to be processed on the HFS stages and thereafter, several parts are joined under the assembly operations based on the predefined Bill of Materials of the product. The aim of this research is to find the schedule which minimises completion time of the last product, i.e. makespan. For the considered problem, lower bound, heuristic algorithms and two metaheuristic techniques based on artificial immune system are developed. Computational results demonstrate that the proposed lower bound and heuristic algorithms outperform the existent lower bounds and heuristic algorithms.

Hybrid intelligent water drops algorithm to unrelated parallel machines scheduling problem: a just-in-time approach

Minimising earliness and tardiness penalties as well as maximum completion time (makespan) simultaneously on unrelated parallel machines is tackled in this research. Jobs are sequence-dependent set-up times and due dates are distinct. Since the machines are unrelated, jobs processing time/cost on different machines may vary, i.e. each job could be processed at different processing times with regard to other machines. A mathematical model which minimises the mentioned objective is proposed which is solved optimally via lingo in small-sized cases. An intelligent water drop (IWD) algorithm, as a new swarm-based nature-inspired optimisation one, is also adopted to solve this multi-criteria problem. The IDW algorithm is inspired from natural rivers. A set of good paths among plenty of possible paths could be found via a natural river in its ways from the starting place (source) to the destination which results in eventually finding a very good path to their destination. A comprehensive computational and statistical analysis is conducted to analyse the algorithms’ performances. Experimental results reveal that the proposed hybrid IWD algorithm is a trustable and proficient one in finding very good solutions, since it is already proved that the IWD algorithm has the property of the convergence in value.

An improved optimization method based on the intelligent water drops algorithm for the vehicle routing problem

We introduce an improved intelligent water drops (IIWD) algorithm as a new swarm-based nature inspired algorithm to solve capacitated vehicle routing problem. IIWD algorithm introduces new adjustments and features that help to optimize the VRP problem with higher efficiency. We reinforce this algorithm to have satisfactory consequences in controlling the balance between diversification and intensification of the search process. We solve 14 well-known benchmark instances in the literature to compare the solutions with the best reported solutions in the literature. Experimental results demonstrate that the suggested technique can well and effectively cope with such problems.

A Hybrid Harmony Search algorithm to minimize total weighted tardiness in the permutation flow shop

We address the permutation flow shop scheduling problem with sequence dependent setup times between jobs. Each job has its weight of importance as well as due date. The goal is to find sequence of jobs such that total weighted tardiness of jobs is minimized. Due to NP-Hard complexity of this problem, a hybrid meta-heuristic algorithm based on Harmony Search Algorithm is developed. In the proposed algorithm, a new acceptance criterion of new improvised harmony is suggested which allows the algorithm to explore the solution space in earlier iterations (diversification), and as algorithm progresses the acceptance criterion leads the algorithm to accept the solutions in neighborhood of the current solution, (intensification). In order to improve the search ability of the algorithm, Variable Neighborhood Search Algorithm is applied to improve the quality of generated harmony. The computational experiments based on well-known benchmark instances are conducted. Results show that the proposed algorithm outperforms other state of the art algorithm used for solving studied problem.

A dynamic virtual hub location problem in airline networks - formulation and metaheuristic solution approaches

Controversial issues in the planning of air transportation networks are inclement weather. These issues cause incapacitation in hub facilities. In this situation, some other kinds of predetermined underutilized facilities in the network are used as virtual hubs to host some or all connections of original hubs to recover the incurred incapacitation and increase network flexibility and demand flow. In this paper, design of our network includes location of virtual hubs (VHs) and routing decision for any origin and destination nodes in the predetermined hub and spoke network in some scheduled periods to exploit the economies of scale. We present a new mathematical model for the dynamic virtual hub location routing problem (DVHLP). The presented model is concerned with minimizing the transportation and maintenance costs. Since the model is a NP-hard one, only small size problems can be solved optimally. Therefore, we propose two efficient metaheuristic approaches (ILS and HSA) to solve the DVHLP. We examine the effectiveness of our approaches using the well-known CAB data set and Turkish networks. Results indicate the better performance of HSA in comparison with ILS in terms of quality and CPU time.

A new cell formation problem with the consideration of multifunctional machines and in-route machines dissimilarity - A two phase solution approach

The purpose of this paper is to develop a variety of cell formation problem (CFP) that considers new concepts. Due to utilizing the machine flexibility causing system flexibility, multifunctional machines are used in the CFP. Machine-operation and part-operation are defined to introduce machine capabilities and part requirements, respectively. A novel solution approach with two phases is presented to solve the considered problem. First phase is a mathematical model proposed to define machines grouping. This model is seeking to minimize in-route machines dissimilarity. Second phase allocated to a heuristic method which assigns parts to corresponding cells. For validation the presented solution approach some test instances are solved: Two critical examples of CFP in [5], and a new one that design to illustrate the complete characteristics of the considered problem. Results show the capability of proposed approach in comparison with other methods to solve the variety of cell formation problems.

Intelligent water drops algorithm on parallel machines scheduling

Maximum completion time so called makespan as well as earliness and tardiness penalties are simultaneously minimized on parallel machines in this paper. An intelligent water drops (IWD) algorithm as a new swarm-based nature inspired optimization one is presented and applied to solve this problem. Experimental results show the superiority of the employed IWD method.

Dynamic Virtual Hub Location Problem

A controversial issue in the planning of air transportation networks is inclement weather. In this situation, hub facilities would not be able to provide a good service to their spoke nodes temporarily. Thus, some other kinds of predetermined underutilized facilities in the network are used as virtual hubs to host some or all connections of original hubs to recover the incurred incapacitation and increase network flexibility and demand flow.Here, we present a dynamic virtual hub location problem with the aim of minimizing transportation cost in the network. We examine the effectiveness of our model using the US well-known CAB data set.