Vicente Valls

Justification and RCPSP: A technique that pays

Abstract The objective of this paper is to show that justification is a simple technique that can be easily incorporated in diverse algorithms for the resource-constrained project scheduling problem––improving the quality of the schedules generated without generally requiring more computing time. The results of incorporating this technique in 22 different algorithms are shown. Fifteen of the new algorithms that use double justification outperform seven of the best heuristic algorithms that do not use justification. The tests have been performed on the standard test set j120 for the RCPSP generated using ProGen.

A hybrid genetic algorithm for the resource-constrained project scheduling problem

Abstract In this paper we propose a Hybrid Genetic Algorithm (HGA) for the Resource-Constrained Project Scheduling Problem (RCPSP). HGA introduces several changes in the GA paradigm: a crossover operator specific for the RCPSP; a local improvement operator that is applied to all generated schedules; a new way to select the parents to be combined; and a two-phase strategy by which the second phase re-starts the evolution from a neighbour’s population of the best schedule found in the first phase. The computational results show that HGA is a fast and high quality algorithm that outperforms all state-of-the-art algorithms for the RCPSP known by the authors of this paper for the instance sets j60 and j120. And that it is competitive with other state-of-the-art heuristics for the instance set j30.

Resource-constrained project scheduling: A critical activity reordering heuristic

Abstract In this paper, we present a new metaheuristic algorithm for the resource-constrained project-scheduling problem. The procedure is a non-standard implementation of fundamental concepts of tabu search without explicitly using memory structures embedded in a population-based framework. The procedure makes use of a fan search strategy to intensify the search, whereas a strategic oscillation mechanism loosely related to the forward/backward technique provides the necessary diversification. Our implementation employs the topological order (TO) representation of schedules. To explore the TO vector space we introduce three types of moves, two of them based on the concept of relative criticality, and a third one based on multi-pass sampling ideas. The strategic utilisation of probabilities for move construction is another distinguishing feature of our approach. Extensive computational testing with more than 2000 problem instances shows the merit of the proposed solution method.

A Population-Based Approach to the Resource-Constrained Project Scheduling Problem

We present a population-based approach to the RCPSP. The procedure has two phases. The first phase handles the initial construction of a population of schedules and these are then evolved until high quality solutions are obtained. The evolution of the population is driven by the alternative application of an efficient improving procedure for locally improving the use of resources, and a mechanism for combining schedules that blends scatter search and path relinking characteristics. The objective of the second phase is to explore in depth those vicinities near the high quality schedules. Computational experiments on the standard j120 set, generated using ProGen, show that our algorithm produces higher quality solutions than state-of-the-art heuristics for the RCPSP in an average time of less than five seconds.

Skilled workforce scheduling in Service Centres

The Skilled Workforce Project Scheduling Problem (SWPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many company Service Centres (SC). The SWPSP considers many real characteristics faced daily by the SC: client-company service quality agreements that establish maximum dates for the beginning and the end of tasks with penalties for delays, criticality levels indicating the client-priority in processing each task, generalized precedence relationships that can produce cycle structures, time period and percentage time lags and variable task durations depending on the worker executing the task. Furthermore, the SC workforce is made up of specialist workers characterised by efficiency levels showing their efficiency and speed executing the several types of tasks. Each worker has his or her own timetable. The main objective of the SWPSP is to quickly obtain a feasible plan of action satisfying maximum established dates and timetable worker constraints. Secondary objectives deal with the urgency levels imposed by the criticality task levels, to obtain well-balanced worker workloads and an efficient assignment of specialists to tasks. In this paper an efficient and quick hybrid genetic algorithm that combines local searches with genetic population management techniques is presented to manage the model.

A double genetic algorithm for the MRCPSP/max

This paper presents a heuristic solution procedure for a very general resource-constrained project scheduling problem. Here, multiple execution modes are available for the individual activities of the project. In addition, minimum as well as maximum time lags between different activities may be given. The objective is to determine a mode and a start time for each activity such that the temporal and resource constraints are met and the project duration is minimised. Project scheduling problems of this type occur e.g. in process industries. The heuristic is a two-phased genetic algorithm with different representation, fitness, crossover operator, etc., in each of them. One of the contributions of the paper is the optimisation in the first phase of a problem dual to the original, the searching for the best modes of the activities. Computational results show that the algorithm outperforms the state-of-the-art algorithms in medium and large instances.

Pre-emption in resource-constrained project scheduling

The Resource-Constrained Project Scheduling Project (RCPSP), together with some of its extensions, has been widely studied. A fundamental assumption in this basic problem is that activities in progress are non-preemptable. Very little effort has been made to uncover the potential benefits of discrete activity pre-emption, and the papers dealing with this issue have reached the conclusion that it has little effect on project length when constant resource availability levels are defined. In this paper we show how three basic elements of many heuristics for the RCPSP - codification, serial SGS and double justification - can be adapted to deal with interruption. The paper is mainly focussed on problem 1_PRCPSP, a generalization of the RCPSP where a maximum of one interruption per activity is allowed. However, it is also shown how these three elements can be further adapted to deal with more general pre-emptive problems. Computational experiments on the standard j30 and j120 sets support the conclusion that pre-emption does help to decrease project length when compared to the no-interruption case. They also prove the usefulness of the justification in the presence of pre-emption. The justification is a RCPS technique that can be easily incorporated into a wide range of algorithms for the RCPSP, increasing their solution quality - maintaining the number of schedules calculated.

Project Scheduling with Stochastic Activity Interruptions

In this chapter we address the problem of scheduling the activities of a resource-constrained project, some of which may be interrupted by an uncertain amount of time. The resources may be, for example, machines in a jobshop, computers with specialized software packages (as those needed for engineering designs), or highly specialized technicians.

A tabu search approach to machine scheduling

Abstract In this paper we apply the tabu search (TS) technique to a complex machine scheduling problem. The problem can be considered as a generalization of the job-shop problem with both simple and parallel machines, job batches, setup times and release and due dates. The goal is to obtain feasible schedules by minimizing the makespan Cm,, if the problem is feasible, or to obtain a “best compromise” schedule if a full solution is not possible. The TS algorithm developed here is distinguished mainly by two aspects. Firstly, the core of the procedure is a tabu thresholding algorithm which uses a sophisticated set of moves aimed at resolving violated constraints. Secondly, the TS algorithm supplements the central tabu thresholding algorithm with two diversification strategies which are dependent on the state of the search. These strategies involve fairly major disruption of the schedules, and force significant diversification of the search. Computational experiments show that our algorithm can find high quality schedules in short running times

A branch and bound algorithm for minimizing the number of crossing arcs in bipartite graphs

Abstract Acyclic directed graphs are widely used in many fields of economic and social sciences. This has generated considerable interest in algorithms for drawing “good” maps of acyclic diagraphs. The most important criterion to obtain a readable map of an acyclic graph is that of minimizing the number of crossing arcs. In this paper, we present a branch and bound algorithm for solving the problem of minimizing the number of crossing arcs in a bipartite graph. Computational results are reported on a set of randomly generated test problems.