On electrical load tracking scheduling for a steel plant

Nolde and Morari (2010) study a steel manufacturing scheduling problem where the tasks must be scheduled such that electricity consumption matches to a pre-specified periodic energy chart. They propose a continuous time integer linear programming formulation to solve the problem. In this note, we present an alternative continuous time formulation, focused on the relative positions of tasks and time periods, that improves significantly the computation time

Project scheduling under uncertainty using fuzzy modelling and solving techniques

In the real world, projects are subject to numerous uncertainties at different levels of planning. Fuzzy project scheduling is one of the approaches that deal with uncertainties in project scheduling problem. In this paper, we provide a new technique that keeps uncertainty at all steps of the modelling and solving procedure by considering a fuzzy modelling of the workload inspired from the fuzzy/possibilistic approach. Based on this modelling, two project scheduling techniques, Resource Constrained Scheduling and Resource Leveling, are considered and generalized to handle fuzzy parameters. We refer to these problems as the Fuzzy Resource Constrained Project Scheduling Problem (FRCPSP) and the Fuzzy Resource Leveling Problem (FRLP). A Greedy Algorithm and a Genetic Algorithm are provided to solve FRCPSP and FRLP respectively, and are applied to civil helicopter maintenance within the framework of a French industrial project called Helimaintenance

Fuzzy uncertainty modelling for project planning; application to helicopter maintenance

Maintenance is an activity of growing interest specially for critical systems. Particularly, aircraft maintenance costs are becoming an important issue in the aeronautical industry. Managing an aircraft maintenance center is a complex activity. One of the difficulties comes from the numerous uncertainties that affect the activity and disturb the plans at short and medium term. Based on a helicopter maintenance planning and scheduling problem, we study in this paper the integration of uncertainties into tactical and operational multiresource, multi-project planning (respectively Rough Cut Capacity Planning and Resource Constraint Project Scheduling Problem). Our main contributions are in modelling the periodic workload on tactical level considering uncertainties in macro-tasks work contents, and modelling the continuous workload on operational level considering uncertainties in tasks durations. We model uncertainties by a fuzzy/possibilistic approach instead of a stochastic approach since very limited data are available. We refer to the problems as the Fuzzy RoughCut Capacity Problem (FRCCP) and the Fuzzy Resource Constraint Project Scheduling Problem (RCPSP).We apply our models to helicopter maintenance activity within the frame of the Helimaintenance project, an industrial project approved by the French Aerospace Valley cluster which aims at building a center for civil helicopter maintenance

Progress in large-shared projects : method for forecasting and optimizing project duration in a distributed project

In large-shared projects, it is still difficult to measure progress due to the complexities involved, because the realization is shared among departments of a company or among companies in the world. Project management and operations research literature is reviewed for discovering various techniques applicable. Widely used tools for progress measurement and forecasting, such as Earned Value Analysis, Progress Plot, Milestone and Resource slip charts, concurrent engineering, can be employed. This paper is based on a problem of pharmaceutical industry where the effectiveness of a certain medical treatment is examined on patients in a number of countries. The number of variables involved increase the complexity of this problem. The main objective is to analyze the effectiveness of a solution in different situations during the project such that a better project duration and a lower cost can be achieved. Our findings suggest that reallocation of patients among countries produces better results in terms of progress

The energy scheduling problem: Industrial case-study and constraint propagation techniques

This paper deals with production scheduling involving energy constraints, typically electrical energy. We start by an industrial case-study for which we propose a two-step integer/constraint programming method. From the industrial problem we derive a generic problem,the Energy Scheduling Problem (EnSP). We propose an extension of specific resource constraint propagation techniques to efficiently prune the search space for EnSP solving. We also present a branching scheme to solve the problem via tree search.Finally,computational results are provided

Tactical project planning under uncertainty: fuzzy approach

At the tactical planning level in a multi-project environment, uncertainties are inherent to the workloads, and costs may be involved for using non-regular capacity and violating project due dates. We propose an approach to identify whether non-regular capacities might be needed to meet the projects' due dates. This problem is known as rough-cut capacity planning (RCCP) problem under uncertainty. We propose a possibilistic approach, which is based on modelling uncertain workloads with fuzzy sets. We present the resulting fuzzy rough-cut capacity planning (FRCCP), and show that we can use the possibilistic approach to provide a robust solution with a fuzzy resource loading profile that supports managers in decision making. We provide a simulated annealing approach to solve the FRCCP, and test it against several existing RCCP approaches. For the experiments we use real life instances from a shipyard maintenance centre

Maintenance planning on French military aircraft operations

The Military Flight and Maintenance Planning Problem considered here aims to assign missions and maintenance tasks to military aircraft. It is a variant of the Flight and Maintenance Planning problem where flights are not modeled geographically since a round-trip to the base is assumed for each flight. It also includes different objectives and constraints

On the integration of Dantzig-Wolfe and Fenchel decompositions via directional normalizations

The strengthening of linear relaxations and bounds of mixed integer linear programs has been an active research topic for decades. Enumeration-based methods for integer programming like linear programming-based branch-and-bound exploit strong dual bounds to fathom unpromising regions of the feasible space. In this paper, we consider the strengthening of linear programs via a composite of Dantzig-Wolfe and Fenchel decompositions. We provide geometric interpretations of these two classical methods. Motivated by these geometric interpretations, we introduce a novel approach for solving Fenchel sub-problems and introduce a novel decomposition combining Dantzig-Wolfe and Fenchel decompositions in an original manner. We carry out an extensive computational campaign assessing the performance of the novel decomposition on the unsplittable flow problem. Very promising results are obtained when the new approach is compared to classical decomposition methods

Ordonnancement d'atelier et ressources humaines: affectation des opérateurs dans un flowshop

Cet article aborde le problème de l'ordonnancement d'un atelier de type flowshop, lorsque les durées opératoires varient suivant quel opérateur travaille sur quelle machine. La prise en compte de cette notion de performance ajoute l'affectation des opérateurs au problème d’ordonnancement, qui ne se résume plus à une recherche de séquence de passage des travaux sur les machines. Une heuristique basée sur une règle d'affectation "intuitive" généralement utilisée est évaluée, puis une borne inférieure du problème complet est présentée. Cette borne permet de faire apparaître certaines caractéristiques des règles d’affectation