• A Hybrid Scatter Search / Electromagnetism Meta-Heuristic for Project Scheduling

      Debels, Dieter; De Reyck, B.; Leus, Roel; Vanhoucke, Mario (2006)
    • A hybrid single and dual population search procedure for the job shop scheduling problem

      Sels, Veronique; Craeymeersch, Kjeld; Vanhoucke, Mario (2011)
    • A metaheuristic solution approach for the time-constrained project scheduling problem

      Verbeeck, Cédric; Van Peteghem, Vincent; Vanhoucke, Mario; Vansteenwegen, Pieter; Aghezzaf, El Houssaine (Springer, 2017)
      In this paper, a metaheuristic solution procedure for the Time-Constrained Project Scheduling Problem is proposed, in which additional resources can be temporarily allocated to meet a given deadline. The problem consists of determining a schedule such that the project is completed on time and that the total additional cost for the resources is minimized. For this problem, an artificial immune system is proposed, in which each solution is represented by a vector of activity start times. A local search procedure, which tries to shift cost causing activities, is applied to each population schedule. Computational experiments are applied to modified resource-constrained project scheduling problem benchmark instances and reveal promising results.
    • A multivariate approach for top-down project control using earned value management

      Colin, Jeroen; Martens, Annelies; Vanhoucke, Mario; Wauters, Mathieu (2015)
      Project monitoring and the related decision to proceed to corrective action are crucial components of an integrated project management and control decision support system (DSS). Earned value management/earned schedule (EVM/ES) is a project control methodology that is typically applied for top-down project schedule control. However, traditional models do not correctly account for the multivariate nature of the EVM/ES measurement system. We therefore propose a multivariate model for EVM/ES, which implements a principal component analysis (PCA) on a simulated schedule control reference. During project progress, the real EVM/ES observations can then be projected onto these principal components. This allows for two new multivariate schedule control metrics (T2 and SPE) to be calculated, which can be dynamically monitored on project control charts. Using a computational experiment, we show that these multivariate schedule control metrics lead to performance improvements and practical advantages in comparison with traditional univariate EVM/ES models.
    • A nearest neighbour extension to project duration forecasting with artificial intelligence

      Wauters, Mathieu; Vanhoucke, Mario (2017)
      In this paper, we provide a Nearest Neighbour based extension for project control forecasting with Earned Value Management. The k-Nearest Neighbour method is employed as a predictor and to reduce the size of a training set containing more similar observations. An Artificial Intelligence (AI) method then makes use of the reduced training set to predict the real duration of a project. Additionally, we report on the forecasting stability of the various AI methods and their hybrid Nearest Neighbour counterparts. A large computer experiment is set up to assess the forecasting accuracy and stability of the existing and newly proposed methods. The experiments indicate that the Nearest Neighbour technique yields the best stability results and is able to improve the AI methods when the training set is similar or not equal to the test set. Sensitivity checks vary the amount of historical data and number of neighbours, leading to the conclusion that having more historical data, from which the a relevant subset can be selected by means of the proposed Nearest Neighbour technique, is preferential.
    • A new scheduling technique for the resource-constrained project scheduling problem with discounted cash flows

      Leyman, Pieter; Vanhoucke, Mario (2015)
      In this paper, we discuss the resource-constrained project scheduling problem with discounted cash flows. We introduce a new schedule construction technique which moves sets of activities to improve the project net present value and consists of two steps. In particular, the inclusion of individual activities into sets, which are then moved together, is crucial in both steps. The first step groups the activities based on the predecessors and successors in the project network, and adds these activities to a set based on their finish time and cash flow. The second step on the contrary does so based on the neighbouring activities in the schedule, which may but need not include precedence related activities. The proposed scheduling method is implemented in a genetic algorithm metaheuristic and we employ a penalty function to improve the algorithm's feasibility with respect to a tight deadline. All steps of the proposed solution methodology are tested in detail and an extensive computational experiment shows that our results are competitive with existing work.
    • A new solution approach to solve the resource-constrained project scheduling problem with logical constraints

      Vanhoucke, Mario; Coelho, José (2016)
      This paper presents a new solution approach to solve the resource-constrained project scheduling problem in the presence of three types of logical constraints. Apart from the traditional AND constraints with minimal time-lags, these precedences are extended to OR constraints and bidirectional (BI) relations. These logical constraints extend the set of relations between pairs of activities and make the RCPSP definition somewhat different from the traditional RCPSP research topics in literature. It is known that the RCPSP with AND constraints, and hence its extension to OR and BI constraints, is NP-hard. The new algorithm consists of a set of network transformation rules that removes the OR and BI logical constraints to transform them into AND constraints and hereby extends the set of activities to maintain the original logic. A satisfiability (SAT) solver is used to guarantee the original precedence logic and is embedded in a metaheuristic search to resource feasible schedules that respect both the limited renewable resource availability as well as the precedence logic. Computational results on two well-known datasets from literature show that the algorithm can compete with the multi-mode algorithms from literature when no logical constraints are taken into account. When the logical constraints are taken into account, the algorithm can report major reductions in the project makespan for most of the instances within a reasonable time.
    • A parallel multi-objective scatter search for optimising incentive contract design in projects

      Kerkhove, Louis-Philippe; Vanhoucke, Mario (2017)
      We present a novel optimisation approach for incentive contract design within a project setting. the structure of the remuneration is one of the key challenges faced by the project owner when (s)he decides to hire a contractor. The proposed technique builds on the recently proposed contract design methodology by Kerkhove and Vanhoucke (Omega, 2015). Specifically, a novel multi-objective scatter search heuristic is proposed and implemented using parallelisation. Both single- and multi-population implementations of this heuristic are compared to the original full-factorial approach as well as commercial optimisation software. The results of the computational experiments indicate that the single-population parallel scatter search procedure significantly outperforms the other solution strategies in terms of both speed and solution quality.
    • A random network generator for activity-on-the-node networks

      Vanhoucke, Mario; Demeulemeester, Erik; Herroelen, Willy (2003)
    • A resource dependence, social network and contingency model of sustainability in supply chain alliances

      Shymko, Yuliya; Diaz, Angel (2012)
      application of other theoretical lenses originating in diverse management disciplines.
    • A resource type analysis of the integrated project scheduling and personnel staffing problem

      Maenhout, Broos; Vanhoucke, Mario (2017)
      In the integrated project scheduling and personnel staffing problem the project activities are scheduled and simultaneously a staffing plan is composed to carry out a single project. In this way, the project schedule that leads to the staffing plan with minimum cost is determined. In this paper, we evaluate different scheduling policies and practices for different personnel resource types. We examine the impact on the staffing cost when the personnel resources are scheduled in a cyclic versus a non-cyclic manner for different (days on, days off)-patterns. Furthermore, the impact of introducing more flexible resource types, such as overtime and temporary help, is explored in relationship with the activity resource demand variability. Computational results show that non-cyclic scheduling leads to a considerable lower staffing cost under all circumstances compared to cyclic scheduling. However, despite the tractability of the resource requirements, flexible temporary resources are essential on top of the regular personnel resources to respond to the variability in demand. The addition of overtime on a strategic staffing level only marginally decreases the personnel cost.
    • A scatter search for the extended resource renting problem

      Vandenheede, Len; Vanhoucke, Mario; Maenhout, Broos (2016)
      In this paper, the extended Resource Renting Problem (RRP/extended) is presented. The RRP/extended is a time-constrained project scheduling problem, in which the total project cost is minimised. In the RRP/extended, this total project cost is determined by a number of extra costs, which are defined in this paper. These costs are based on the costs that are used in the traditional Resource Renting Problem and the Total Adjustment Cost Problem. Therefore, the RRP/extended represents a union of these two problems. To solve the RRP/extended, a scatter search is developed. The building blocks of this scatter search are specifically designed for the RRP/extended. We introduce two crossovers and an improvement method. The efficiency of these building blocks will be shown in the paper. Furthermore, a sensitivity analysis is presented in which the five costs have diverse values.
    • A study of the stability of earned value management forecasting

      Wauters, Mathieu; Vanhoucke, Mario (2015)
      In this paper, the authors focus on the stability of earned value management (EVM) forecasting methods. The contribution is threefold. First of all, a new criterion to measure stability that does not suffer from the disadvantages of the historically employed concept is proposed. Second, the stability of time and cost forecasting methods is compared and contrasted by means of a computational experiment on a topologically diverse data set. Throughout these experiments, the forecasting accuracy is reported as well, facilitating a trade-off between accuracy and stability. Finally, it is shown show that the novel stability metric can be used in practical environments using two real-life projects. The conclusions of this empirical validation are found to be largely in line with the computational results.
    • A study on complexity and uncertainty perception and solution strategies for the time/cost trade-off problem

      Wauters, Mathieu; Vanhoucke, Mario (2016)
      In this article, the Discrete Time/Cost Tradeoff Problem (DTCTP) is revisited in light of a student experiment. Two solution strategies are distilled from the data of 444 participants and are structured by means of five building blocks: focus, activity criticality, ranking, intensity, and action. The impact of complexity and uncertainty on the cost objective is quantified in a large computational experiment. Specific attention is allocated to the influence of the actual and perceived complexity and uncertainty and the cost repercussions when reality and perception do not coincide.