A hybrid scatter search. Electromagnetism meta-heuristic for project scheduling.

In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the effectiveness of exact optimisation to relatively small instances. In this paper, we present a new meta-heuristic for this problem, able to provide near-optimal heuristic solutions. The procedure combines elements from scatter search, a generic population-based evolutionary search method, and a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory, hereafter referred to as the electromagnetism meta-heuristic. We present computational experiments on standard benchmark datasets, compare the results with current state-ofthe-art heuristics, and show that the procedure is capable of producing consistently good results for challenging instances of the resource-constrained project scheduling problem. We also demonstrate that the algorithm outperforms state-of-the-art existing heuristics.Algorithms; Effectiveness; Electromagnetism; Functions; Heuristic; Project scheduling; Scatter; Scatter search; Scheduling; Theory;

Welcome to OR&S! Where students, academics and professionals come together

In this manuscript, an overview is given of the activities done at the Operations Research and Scheduling (OR&S) research group of the faculty of Economics and Business Administration of Ghent University. Unlike the book published by [1] that gives a summary of all academic and professional activities done in the field of Project Management in collaboration with the OR&S group, the focus of the current manuscript lies on academic publications and the integration of these published results in teaching activities. An overview is given of the publications from the very beginning till today, and some of the topics that have led to publications are discussed in somewhat more detail. Moreover, it is shown how the research results have been used in the classroom to actively involve students in our research activities

Heuristics for the distributed blocking Ffow shop scheduling problem

Postprint (published version

Comparison Between Genetic Algorithm and Electromagnetism-Like Algorithm for Solving Inverse Kinematics

A comparison study between Electromagnetism-Like Algorithm (EM) and Genetic Algorithm (GA)has been presented in this work to solve the Inverse Kinematics (IK) of a four-link planar robot manipulator. The comparison is focused on some points for both algorithms like the accuracy of the results and the speed of convergence. Different target points have been taken to check the performance of each algorithm to solve the IK problem. The results showed that EM algorithm needs less population size and number of generations to get the true solution. There are multiple robot configurations at the goal points and both algorithms are able to find these solutions at each point. Self developed software simulator is used to display some of these solutions at each goal position

Optimization Algorithms in Project Scheduling

Scheduling, or planning in a general perspective, is the backbone of project management; thus, the successful implementation of project scheduling is a key factor to projects’ success. Due to its complexity and challenging nature, scheduling has become one of the most famous research topics within the operational research context, and it has been widely researched in practical applications within various industries, especially manufacturing, construction, and computer engineering. Accordingly, the literature is rich with many implementations of different optimization algorithms and their extensions within the project scheduling problem (PSP) analysis field. This study is intended to exhibit the general modelling of the PSP, and to survey the implementations of various optimization algorithms adopted for solving the different types of the PSP

Local search Methods to Solve The Sum of Two Objective Functions

In this paper, the problem of sequencing a set of n jobs on single machine was considered to minimize theobjective function. The aim  is to find the optimal or near optimal  solution  (scheduling) for the objective function consists of a  sum  of  total late work and maximum lateness. This problem is strongly NP-hard. Simulated Annealing, Ant colony Algorithm, and usagea hybridization as a tool to solved the problem approximatelywith up to  100000 jobs in a reasonable time 10 minutes

Optimal resource allocation in stochastic activity networks via the electromagnetism approach: a platform implementation in Java

An optimal resource allocation approach to stochastic multimodal projects had been previously developed by applying a Dynamic Programming model which proved to be very demanding computationally. A new approach, the Electromagnetism-like Mechanism, has also been adopted and implemented in Mat lab, to solve this problem. This paper presents the implementation of the Electromagnetism approach using an Object Oriented language, Java, and a distributed version to be run in a computer network, in order to take advantage of available computational resources.info:eu-repo/semantics/publishedVersio

Efficient constructive procedures for the distributed blocking flowshop scheduling problem

the distributed blocking flow shop scheduling problem (DBFSP) allows modeling of the scheduling process in companies with more than one factory, with productive systems configured as flow shop lines where the blocking constraint has to be considered. To the best of our knowledge, this variant of the distributed permutation flow shop scheduling problem has not been studied. In this paper, we propose some constructive heuristics that will solve the DBFSP and thus minimize the maximum completion time among the factories. The proposed procedures use two approaches that are totally different from those proposed for the distributed permutation flow shop scheduling problem (DPFSP). By taking the DPFSP procedures that we adapted to DBFSP and comparing them to the new approaches that were specifically designed for DBPFSP, we find that the latter perform considerably better.Postprint (published version