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Abstrak :
ABSTRAK
Masalah penjadwalan adalah salah satu masalah klasik optimasi kombinatorial yang ada di berbagai segi seperti sistem manufaktur fleksibel, perencanaan produksi, industri penerbangan, dll. Baru-baru ini, beberapa algoritma yang efektif untuk optimasi global dan memecahkan masalah penjadwalan proyek telah diterapkan. Meta-heuristik adalah sistem cerdas, proses iteratif/perulangan yang menekankan pada proses pencarian dan dapat diterapkan terhadap masalah optimasi, seperti masalah mesin tunggal. Algoritma Elektromagnetisme-Like Mechanism (EM) berbasis populasi meta-heuristik yang telah diusulkan untuk memecahkan masalah yang berkelanjutan secara efektif. Pendekatan baru ini mencoba untuk mencapai efek konvergensi dan keragaman ketika iteratif diterapkan untuk memecahkan masalah. Algoritma ini diuji secara komputasi dan hasil perhitungan menunjukkan bahwa algoritma ini melakukan lebih baik daripada aturan penjadwalan sederhana, seperti metode penjadwalan EDD (Earliest Due Date), SPT (Shortest Processing Time) dan LPT (Largest Processing Time).

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Abstract
Scheduling problem are one of the classical combinatorial optimisation problems which exist in many diverse areas such as flexiblemanufacturing systems, production planning, air lane industry, etc. Recently, several effective algorithms for global optimization and solving the resource-constrained project scheduling problem have been proposed. A Meta-heuristics is an intelligent, iterative process that guides a search and can be applied towards optimization problem, such as the single machine problem. An Electromagnetism-like Mechanism (EM) Algorithm is a populationbased meta-heuristic which has been proposed to solve continuous problems effectively. This new approach attempts to achieve the convergence and diversity effects when it is iteratively applied to solve the problem. This algorithm is tested on the computational results show that this algorithm performs better than the simple scheduling rules, such as EDD (Earliest Due Date) scheduling method, SPT (Shortest Processing Time) and LPT (Largest Processing Time) scheduling method.

Abstrak :
This book is the first contemporary comprehensive treatment of optimization without derivatives, and it covers most of the relevant classes of algorithms from direct-search to model-based approaches. Readily accessible to readers with a modest background in computational mathematics, Introduction to Derivative-Free Optimization contains: 1. a comprehensive description of the sampling and modeling tools needed for derivative-free optimization that allow the reader to better understand the convergent properties of the algorithms and identify their differences and similarities; 2.analysis of convergence for modified Nelderead and implicit-filtering methods as well as for model-based methods such as wedge methods and methods based on minimumorm Frobenius models.