Adaptation and parameters studies of CS algorithm for flow shop scheduling problem

Scheduling concerns the allocation of limited resources overtime to perform tasks to fulfill certain criterion and optimize one or several objective functions. One of the most popular models in scheduling theory is that of the flow-shop scheduling. During the last 40 years, the permutation flow-shop sequencing problem with the objective of makespan minimization has held the attraction of many researchers. This problem characterized as Fm/prmu/Cmax in the notation of Graham, involves the determination of the order of processing of n jobs on m machines. In addition, there was evidence that m-machine permutation flow-shop scheduling problem (PFSP) is strongly NP-hard for m ≥3. Due to this NP-hardness, many heuristic approaches have been proposed, this work falls within the framework of the scientific research, whose purpose is to study Cuckoo search algorithm. Also, the objective of this study is to adapt the cuckoo algorithm to a generalized permutation flow-shop problem for minimizing the total completion time, so the problem is denoted as follow: Fm | | Cmax. Simulation results are judged by the total completion time and algorithm run time for each instance processed

A Literature Review of Cuckoo Search Algorithm

Optimization techniques play key role in real world problems. In many situations where decisions are taken based on random search they are used. But choosing optimal Optimization algorithm is a major challenge to the user. This paper presents a review on Cuckoo Search Algorithm which can replace many traditionally used techniques. Cuckoo search uses Levi flight strategy based on Egg laying Radius in deriving the solution specific to problem. CS optimization algorithm increases the efficiency, accuracy, and convergence rate. Different categories of the cuckoo search and several applications of the cuckoo search are reviewed. Keywords: Cuckoo Search Optimization, Applications , Levy Flight DOI: 10.7176/JEP/11-8-01 Publication date:March 31st 202

Comparison of new metaheuristics, for the solution of an integrated jobs-maintenance scheduling problem

This paper presents and compares new metaheuristics to solve an integrated jobs-maintenance scheduling problem, on a single machine subjected to aging and failures. The problem, introduced by Zammori et al. (2014), was originally solved using the Modified Harmony Search (MHS) metaheuristic. However, an extensive numerical analysis brought to light some structural limits of the MHS, as the analysis revealed that the MHS is outperformed by the simpler Simulated Annealing by Ishibuchi et al. (1995). Aiming to solve the problem in a more effective way, we integrated the MHS with local minima escaping procedures and we also developed a new Cuckoo Search metaheuristic, based on an innovative Levy Flight. A thorough comparison confirmed the superiority of the newly developed Cuckoo Search, which is capable to find better solutions in a smaller amount of time. This an important result, both for academics and practitioners, since the integrated job-maintenance scheduling problem has a high operational relevance, but it is known to be extremely hard to be solved, especially in a reasonable amount of time. Also, the developed Cuckoo Search has been designed in an extremely flexible way and it can be easily readapted and applied to a wide range of combinatorial problems. (C) 2018 Elsevier Ltd. All rights reserved

Application of an evolutionary algorithm-based ensemble model to job-shop scheduling

In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. The MmGA ensemble is able to approximate the optimal solution under the Pareto optimality principle. To evaluate the effectiveness of the MmGA ensemble, a case study based on real requirements is conducted. The results positively indicate the effectiveness of the MmGA ensemble in undertaking job-shop scheduling problems

Discrete penguins search optimization algorithm to solve flow shop scheduling problem

Flow shop scheduling problem is one of the most classical NP-hard optimization problem. Which aims to find the best planning that minimizes the makespan (total completion time) of a set of tasks in a set of machines with certain constraints. In this paper, we propose a new nature inspired metaheuristic to solve the flow shop scheduling problem (FSSP), called penguins search optimization algorithm (PeSOA) based on collaborative hunting strategy of penguins.The operators and parameter values of PeSOA redefined to solve this problem. The performance of the penguins search optimization algorithm is tested on a set of benchmarks instances of FSSP from OR-Library, The results of the tests show that PeSOA is superior to some other metaheuristics algorithms, in terms of the quality of the solutions found and the execution time

Cuckoo Search Algorithm untuk Menyelesaikan Bi-Objective Permutation Flowshop Scheduling Problem

Tujuan dari penelitian ini adalah menyelesaikan permasalahan Bi-objective Permutation Flowshop Scheduling Problem (BPFSP) menggunakan Cuckoo Search Algorithm (CSA). BPFSP memiliki lebih dari satu fungsi tujuan yaitu meminimalkan makespan dan total tardiness. Program penerapan CSA untuk menyelesaikan BPFSP diimplementasikan dalam kasus dengan tiga jenis data yaitu data kecil dengan 5-pekerjaan 4-mesin, data sedang dengan 20-pekerjaan 10-mesin, dan data besar 50-pekerjaan 20-mesin dengan penggunaan beberapa nilai parameter yang bervariasi diantaranya maksimum iterasi, banyaknya sarang serta probabilitas pergantian sarang. Berdasarkan hasil running pada ketiga jenis data diperoleh bahwa semakin banyak jumlah sarang serta iterasi maka akan memberikan nilai fungsi tujuan BPFSP yang cenderung lebih baik. Sebaliknya, nilai fungsi tujuan BPFSP akan cenderung lebih baik jika nilai probabilitas pergantian sarang semakin kecil