0360-8352/$ see front matter 2008 Elsevier Ltd. A doi:10.1016/j.cie.2008.07.021 * Corresponding author. E-mail address: [email protected] (X. Shao). Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. Although the traditional optimization algorithms could obtain preferable results in solving the monoobjective FJSP. However, they are very d...

This is a summary of the journal article (Malapert et al. 2012) published by Journal on Computing entitled “An Optimal Constraint Programming Approach to the Open-Shop Problem”. The article presents an optimal constraint programming approach for the Open-Shop scheduling problem, which integrates recent constraint propagation and branching techniques with new upper bound heuristics. Randomized r...

The job shop scheduling problem JSSP is a notoriously difficult problem in combinatorial optimization. In terms of the objective function, most existing research has been focused on the makespan criterion. However, in contemporary manufacturing systems, due-date-related performances are more important because they are essential for maintaining a high service reputation. Therefore, in this study...

The PEGS (Production and Environmental Generic Scheduler) program is a new generic scheduling program for manufacturing companies. It includes sort and search algorithms and can operate on the basis of elapsed time or economic values. Program performance is compared to a series of published benchmarks. The case study presented here illustrates the use of PEGS for a flow shop configuration at a ...

This paper proposes a new and efficient hybrid heuristic scheme for solving job-shop scheduling problems (JSP). A new and efficient population initialization and local search concept, based on genetic algorithms, is introduced to search the solution space and to determine the global minimum solution to the JSP problem. Simulated results imply that the proposed novel JSP method (called the PLGA ...

Flexible assembly job shop scheduling has been proved to be an NP-hard problem. To reduce the complexity, it is always divided into 2 sub-problems: routing sub-problem and sequencing sub-problem. In this paper, in order to develop a solution with high accuracy, we propose a method that can deal with these two sub-problems concurrently. Tabu search, one of the meta-heuristics, is adopted. Some e...

Abstract We consider the single machine scheduling problem with resource dependent release times and processing times, in which both the release times and processing times are strictly linear decreasing functions of the amount of resources consumed. The objective is to minimize the makespan plus the total resource consumption costs. We propose a heuristic algorithm for the general problem by ut...

Iterative flattening search (IFS) is an iterative improvement heuristic schema for makespan minimization in scheduling problems. Given an initial solution, IFS iteratively interleaves a relaxation-step, which randomly retracts some search decisions, and an incremental solving step (or flattening-step) to recompute a new solution. The process continues until a stop condition is met and the best ...

Combinatorial optimization problems are often used to test heuris-tics. Among heuristics, stochastic ones deserve particular consideration being generally meta-heuristics that aim at performing reasonnably well on a wide spectrum of problems. Among them, evolutionary algorithms have recently appeared. Emphasis have been put on them by researches that have shown that they are able to solve eecie...

Distributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power consumption due to inefficient resource management. Task scheduling module as a key component can has drastic impact on both user...