A Cluster-based Evolutionary Algorithm for the Single Machine Total Weighted Tardiness-scheduling Problem

In this paper a new evolutionary algorithm is described for the single machine total weighted tardiness problem. The operation of this method can be divided in three stages: a cluster forming and two local search stages. In the first stage it approaches some locally optimal solutions by grouping based on similarity. In the second stage it improves the accuracy of the approximation of the solutions with a local search procedure while periodically generating new solutions. In the third stage the algorithm continues the application of the local search procedure. We tested our algorithm on all the benchmark problems of ORLIB. The algorithm managed to find, within an acceptable time limit, the best-known solution for the problems, or found solutions within 1% of the best-known solutions in 99 % of the tasks

Dominance-Based Heuristics for One-Machine Total Cost Scheduling Problems

International audienceWe study the one-machine scheduling problem with release dates and we look at several objective functions including total (weighted) tardiness and total (weighted) completion time. We describe dominance rules for these criteria, as well as techniques for using these dominance rules to build heuristic solutions. We use them to improve certain well-known greedy heuristic algorithms from the literature. Finally, we introduce a Tabu Search method with a neighborhood based on our dominance rules. Experiments show the effectiveness of our techniques in obtaining very good solutions for all studied criteria

A simple, fast, and effective heuristic for the single-machine total weighted tardiness problem

We consider the non-preemptive single-machine total weighted tardiness (TWT) problem with general weights, processing times, and due dates. We first develop a family of preemptive lower bounds for this problem and explore their structural properties. Then, we show that the solution corresponding to the least tight lower-bound among those investigated features some desirable properties that can be exploited to build excellent feasible solutions to the original non-preemptive problem in short computational times. We present results on standard benchmark instances from the literature

Matheuristics: using mathematics for heuristic design

Matheuristics are heuristic algorithms based on mathematical tools such as the ones provided by mathematical programming, that are structurally general enough to be applied to different problems with little adaptations to their abstract structure. The result can be metaheuristic hybrids having components derived from the mathematical model of the problems of interest, but the mathematical techniques themselves can define general heuristic solution frameworks. In this paper, we focus our attention on mathematical programming and its contributions to developing effective heuristics. We briefly describe the mathematical tools available and then some matheuristic approaches, reporting some representative examples from the literature. We also take the opportunity to provide some ideas for possible future development

Cyclic scheduling of perishable products in parallel machine with release dates, due dates and deadlines

This paper deals with a realistic cyclic scheduling problem in the food industry environment in which parallel machines are considered to process perishable jobs with given release dates, due dates and deadlines. Jobs are subject to post-production shelf life limitation and must be delivered to retailers during the corresponding time window bounded by due dates and deadlines. Both early and tardy jobs are penalized by partial weighted earliness/tardiness functions and the overall problem is to provide a cyclic schedule of minimum cost. A mixed integer programming model is proposed and a heuristic solution beside an iterated greedy algorithm is developed to generate good and feasible solutions for the problem. The proposed MIP, heuristic and iterated greedy produce a series of solutions covering a wide range of cases from slow optimal solutions to quick and approximated schedules.Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "RESULT - Realistic Extended Scheduling Using Light Techniques" with reference DPI2012-36243-C02-01 co-financed by the European Union and FEDER funds and by the Universitat Politecnica de Valencia, for the project MRPIV with reference PAID/2012/202.Shirvani, N.; Ruiz García, R.; Shadrokh, S. (2014). Cyclic scheduling of perishable products in parallel machine with release dates, due dates and deadlines. International Journal of Production Economics. 156:1-12. https://doi.org/10.1016/j.ijpe.2014.04.013S11215

An overview of neighbourhood search metaheuristics

This paper gives details of the steps needed to undertake neighbourhood search for a combinatorial optimization problem. The main variations are briefly described and pointers for future research briefly discussed. Throughout there is extensive referencing to some of the most important publications in the are

Scheduling en línea minimizando la tardanza total ponderada para una máquina mediante metaheurística Grasp

Programar actividades es una tarea que consciente o inconscientemente todos aplicamos para planear nuestras actividades diarias. Para cualquier persona se hace necesario plantear y evaluar el orden en las que éstas deben ser desarrolladas dependiendo de factores externos y el criterio único del individuo. De igual forma, la planeación de la producción en la industria requiere organizar los trabajos de una manera óptima para aprovechar al máximo unos recursos limitados (máquinas por ejemplo) y cumplir con objetivos enmarcados por la estrategia de la organización (un ejemplo es la política Just-in-Time). Sin embargo, a diferencia de un individuo, la industria cuenta con especializadas herramientas analíticas cuyo único propósito es apoyar a la toma de decisiones, y a lo que se conoce comúnmente dentro del campo de la investigación de operaciones como scheduling.Ingeniero (a) IndustrialPregrad