Modeling and algorithm for resource-constrained multi-project scheduling problem based on detection and rework

Purpose To meet the requirement of establishing an effective schedule for the assembly process with overall detection and rework, this paper aims to address a new problem named resource-constrained multi-project scheduling problem based on detection and rework (RCMPSP-DR). Design/methodology/approach First, to satisfy both online and offline scheduling, a mixed integer programming model is established with a weighted bi-objective minimizing the expected makespan and the solution robustness. Second, an algorithm that combines a tabu search framework with a critical chain-based baseline generation scheme is designed. The tabu search framework focuses on searching for a reasonable resource flow representing the execution sequence of activities, while the critical chain-based baseline generation scheme establishes a buffered baseline schedule by estimating the tradeoff between two aspects of bi-objective. Findings The proposed algorithm can get solutions with gaps from −4.45% to 2.33% when compared with those obtained by the commercial MIP solver CPLEX. Moreover, the algorithm outperforms four other algorithms in terms of both objective performance and stability over instances with different weighting parameters, which reveals its effectiveness. Originality/value The represented RCMPSP-DR considering the overall detection and rework is an extension of the scheduling problem for large-scale equipment. An effective algorithm is proposed to establish the baseline schedule and determine the execution sequence of activities for the assembly process, which is significant for practical engineering applications.

A MATHEMATICAL MODEL FOR DYNAMIC PROJECT SCHEDULING PROBLEM AND REACTIVE SCHEDULING IMPLEMENTATION

In today's real-life implementations, projects are executed under uncertainty in a dynamic environment. In addition to resource constraints, the baseline schedule is affected due to the unpredictability of the dynamic environment. Uncertainty-based dynamic events experienced during project execution may change the baseline schedule partially or substantially and require projects' rescheduling. In this study, a mixed-integer linear programming model is proposed for the dynamic resource-constrained project scheduling problem. Three dynamic situation scenarios are solved with the proposed model, including machine breakdown, worker sickness, and electricity power cut. Finally, generated reactive schedules are completed later than the baseline schedule.

Classification of Evaluation Metrics for Project Baseline Schedules

The Evaluation of construction baseline schedules aims to provide a high-quality project schedule. However, obtaining a project schedule free from technical defects remains a challenge to construction planners and schedulers.The result of having a high-quality schedule is achieving the desired project completion dates and avoid any disputes between the construction project parties which may be present due to the technical defects of the schedule itself. Many organizations and consultants had developed some evaluations techniques for assessing the baseline schedules from different prospects. The aim of this study is to classify and filter out the evaluation metrics and parameters of the project baseline schedule, in order to facilitate the schedule reviewing and evaluating process. This is achieved by introducing a clear, arranged and classified evaluation metrics to let the schedule reviewerto list down all the schedule technical defects and convert them into clear comments in order to rectify them and having a schedule free of defects.

ESTIMATING NORMAL DURATION OF RENOVATION FOR MULTISTORY APARTMENT BUILDING CONSIDERING EXTENSION-TYPE RENOVATION PROJECTS

Normal (typical) project duration is estimated at the initial stage of a renovation project and is an important reference for project control. However, its estimation has not been researched extensively owing to the complexity and uncertainties of renovation. Thus, a model was developed for predicting the duration of sustainable apartment renovation. Experts were asked to estimate a baseline schedule for extension-type renovation projects, factors that influence critical path activities, and the range of project durations considering these factors. An equation for estimating the duration of a renovation project was developed, and the range of project durations was derived using a MCS to reflect uncertainty. The proposed model was validated by applying it to actual cases. The case study shows that the model would be more suitable for complex renovation construction (i.e., more than two buildings or vertical extension). The model can be applied to various renovation projects and used as a reference for determining contract time. It can fill the knowledge gap of construction duration forecasting by adapting the concept of control activities to simplify the assessment of uncertainties in renovation of apartments, and can be applied for forecasting sustainable renovation time for other project types or in other locations.

Tracking Predictive Gantt Chart for Proactive Rescheduling in Stochastic Resource Constrained Project Scheduling

Proactive-reactive scheduling is important in the situations where the project collaborators need to coordinate their efforts. The coordination is mostly achieved through the combination of the shared baseline schedule and the deviation penalties. In this paper, we present an extension of predictive Gantt chart to the proactive-reactive scheduling needs. It can be used to track the evolution of the relationship between dynamic and static elements through the time. The dynamic elements are evolving probability distributions due to the uncertainty and revealed information. The static elements are time-agreements in the baseline schedule. We demonstrate that in the state-of-the-art proactive-reactive scheduling, the baseline schedule is agnostic to the information received during the project execution. The sources of such inflexibility in the problem model and the scheduling methods are analyzed. The visualization is highlighted as a precursor to developing new methods that proactively change the baseline schedule in accordance with the gained information.

A Proactive Robust Scheduling Method for Aircraft Carrier Flight Deck Operations with Stochastic Durations

The operations on the aircraft carrier flight deck are carried out in a time-critical and resource-constrained environment with uncertainty, and it is of great significance to optimize the makespan and obtain a robust schedule and resource allocation plan for a greater sortie generation capacity and better operational management of an aircraft carrier. In this paper, a proactive robust optimization method for flight deck scheduling with stochastic operation durations is proposed. Firstly, an operation on node-flow (OONF) network is adopted to model the precedence relationships of multi-aircraft operations, and resource constraints categorized into personnel, support equipment, workstation space, and supply resource are taken into consideration. On this basis, a mathematical model of the robust scheduling problem for flight deck operation (RSPFDO) is established, and the goal is to maximize the probability of completing within the limitative makespan (PCLM) and minimize the weighted sum of expected makespan and variance of makespan (IRM). Then, in terms of proactive planning, both serial and parallel schedule generation schemes for baseline schedule and robust personnel allocation scheme and equipment allocation adjustment scheme for resource allocation are designed. In terms of executing schedules, an RSPFDO-oriented preconstraint scheduling policy (CPC) is proposed. To optimize the baseline schedule and resource allocation, a hybrid teaching-learning-based optimization (HTLBO) algorithm is designed which integrates differential evolution operators, peak crossover operator, and learning-automata-based adaptive variable neighborhood search strategy. Simulation results shows that the HTLBO algorithm outperforms both some other state-of-the-art algorithms for deterministic cases and some existing algorithms for stochastic project scheduling, and the robustness of the flight deck operations can be improved with the proposed resource allocation schemes and CPC policy.

Modelling of tri-parameter bidding integrating cost, time and risk: a stochastic approach

Purpose This paper aims to propose a new tri-parameter bidding model integrating cost, time and risk. The key value of the model is that it remains within the framework of the competitive bidding system while controlling the risk resulting from float loss. Design/methodology/approach The model utilizes stochastic scheduling to quantify the float loss impact at the project level. Prospective bidders are evaluated based on their total combined bid (TCB) including cost, time and risk. The risk parameter is calculated as the relative risk between the bidder’s schedule and the client’s baseline schedule. Findings The results confirmed that choosing the contractor based on the lowest price and time reduces the available float and increases the schedule risks. The probability of completing the project on time dropped from 46 per cent for the baseline schedule to 19 per cent for the bidder with the most compressed schedule. The selected bidder, using the proposed model, has the lowest TCB of cost, time and risk. Results show that adding the risk parameter in the evaluation changed the ranking of the bidders. Research limitations/implications The model does not discuss all project risks that the contractor retains. It focuses on schedule risks that result from shortening project duration. The model focuses on solving the problem with price plus time bidding method by addressing the schedule risk issue. Other criteria, such as sustainability, are not considered. Practical implications The proposed model encourages contractors to pay more attention to the time parameter and the schedule risks resulting from aggressive reduction in project duration. Originality/value Problems arose, in the current complex construction industry, as owners rely solely on price as the award criterion. Recently, the bi-parameter bidding system, A + B, introduced the time parameter to the awarding criteria. However, reducing the project duration by compressing the schedule consumes the float of non-critical activities, which reduces the schedule flexibility of a project. The proposed model allows clients to evaluate potential bidders objectively. Rather than evaluating the bidders based on price, in the conventional low bid system, or based on price and time, as in the A + B system, the bidders are evaluated based on three parameters: price, time and risk.