Exact/heuristic hybrids using rVNS and hyperheuristics for workforce scheduling

In this paper we study a complex real-world workforce scheduling problem. We propose a method of splitting the problem into smaller parts and solving each part using exhaustive search. These smaller parts comprise a combination of choosing a method to select a task to be scheduled and a method to allocate resources, including time, to the selected task. We use reduced Variable Neighbourhood Search (rVNS) and hyperheuristic approaches to decide which sub problems to tackle. The resulting methods are compared to local search and Genetic Algorithm approaches. Parallelisation is used to perform nearly one CPU-year of experiments. The results show that the new methods can produce results fitter than the Genetic Algorithm in less time and that they are far superior to any of their component techniques. The method used to split up the problem is generalisable and could be applied to a wide range of optimisation problems

Design of a decision support system for multiobjective activity planning and programming using global bacteria optimization

The success of any project lies in a great manner on keeping costs in the estimated values, as well as meeting customer required due date. Therefore, there is a current need of developing an information system that facilitates the creation and managing of projects and their processes, including costing schemes, as well as monitoring an optimizing project’s makespan. In order to address this situation a user-friendly information system (IS) was developed. This IS includes an optimization module that reduces the project’s execution time, thus, minimizing costs and ultimately providing the manager with the right tools for the correct development of the project. Therefore, a better planning of activities in a reduced time is accomplished. In this way, the project manager is equipped with a decision support system (DSS) that allows a better decision making and, thanks to this performance optimization, a cost-effective solution can be delivered to the company. The optimization module is the main innovative component in this IS, considering that addresses the problem as a multiobjective one, considering at the same time makespan and cost. This module is based on global bacteria optimization (GBO). This becomes the most relevant improvement when compared to other ISs in the market

Criticality Analysis of Activity Networks under Interval Uncertainty

Dedicated to the memory of Professor Stefan Chanas - The extended abstract version of this paper has appeared in Proceedings of 11th International Conference on Principles and Practice of Constraint Programming (CP2005) ("Interval Analysis in Scheduling", Fortin et al. 2005)International audienceThis paper reconsiders the Project Evaluation and Review Technique (PERT) scheduling problem when information about task duration is incomplete. We model uncertainty on task durations by intervals. With this problem formulation, our goal is to assert possible and necessary criticality of the different tasks and to compute their possible earliest starting dates, latest starting dates, and floats. This paper combines various results and provides a complete solution to the problem. We present the complexity results of all considered subproblems and efficient algorithms to solve them