229 research outputs found

    The Multimode Resource Constrained Project Scheduling Problem for Repetitive Activities in Construction Projects

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    [EN] In construction projects, resource availability might limit the implementation of ideal schedules. Especially, when repetitive activities are involved, traditional resource¿constrained project scheduling problem (RCPSP) models fail to allocate the resource consumption in an efficient manner. Besides, actual models only provide local optimal solutions and do not incorporate activity acceleration routines. To fulfill this gap, partially, a mathematical optimization model, the multimode RCPSP for repetitive activities in construction projects, is proposed and solved to optimality; it takes into account acceleration routines under real construction scenarios using spreadsheets. The article shows a complete computational experimentation over a real construction project, considering several scenarios of resource availabilities and continuity conditions. The model allows analyzing the resources efficiency indexes comparing them to resource consumptions, continuity of activities, and objective functions that reveal that fragmented activities do not provide better resource efficiency outcomes.This research was partially supported by the FAPA program of Universidad de Los Andes, Colombia (code P14.246922.005/01). The authors would also like to thank the research group of Construction Engineering and Management (INgeco) at Universidad de los Andes.García-Nieves, J.; Ponz-Tienda, JL.; Salcedo-Bernal, A.; Pellicer Armiñana, E. (2018). The Multimode Resource Constrained Project Scheduling Problem for Repetitive Activities in Construction Projects. Computer-Aided Civil and Infrastructure Engineering. 33(8):655-671. https://doi.org/10.1111/mice.12356S65567133

    Time-Cost Tradeoff and Resource-Scheduling Problems in Construction: A State-of-the-Art Review

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    Duration, cost, and resources are defined as constraints in projects. Consequently, Construction manager needs to balance between theses constraints to ensure that project objectives are met. Choosing the best alternative of each activity is one of the most significant problems in construction management to minimize project duration, project cost and also satisfies resources constraints as well as smoothing resources. Advanced computer technologies could empower construction engineers and project managers to make right, fast and applicable decisions based on accurate data that can be studied, optimized, and quantified with great accuracy. This article strives to find the recent improvements of resource-scheduling problems and time-cost trade off and the interacting between them which can be used in innovating new approaches in construction management. To achieve this goal, a state-of-the-art review, is conducted as a literature sample including articles implying three areas of research; time-cost trade off, constrained resources and unconstrained resources. A content analysis is made to clarify contributions and gaps of knowledge to help suggesting and specifying opportunities for future research

    A genetic algorithm-based method for solving multi-mode resource-constrained project scheduling problem in uncertain environment

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    Project scheduling models with resource constraints and multi-mode activities aims to create a schedule for carrying out activities considering precedence constraints and available resources in order to minimize the project duration. In the real world, we face uncertainty related to projects, where there are no historical data, hence, we should rely on the experts' judgements to estimate activity durations. For this purpose, in this paper, the 99-simulation method is used to deal with uncertainty. The exact mathematical programming model is presented in this paper and the hybrid algorithm based on Genetic Algorithm is used to solve this type of project scheduling problem which finds the near-optimal solution in a short computational time. Finally, the effectiveness of the proposed model is examined with a numerical example.Peer reviewedFinal article published.MRCPSPSimulationUncertaintyGenetic algorith

    Comprehensive Repetitive Scheduling for Linear and Scattered Infrastructure Projects

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    The majority of civil infrastructure projects involve activities that are repeated across a number of units (e.g., linear highway sections; or scattered multi-bridge repairs). While repetition represents a potential for benefiting from the economy of scale, reality is far different and infrastructure projects continue to exhibit large cost overruns, delays, and disputes. With existing solutions for scheduling repetitive projects unable to adequately cater to infrastructure projects, more efficient tools are needed to support efficient planning and resource management for such projects. To address this need, this research introduces a comprehensive scheduling framework able to address the unique challenges and decision-support requirements for linear and scattered projects. The framework presented improves on the existing integrated critical path method & line-of-balance repetitive scheduling formulation to better achieve synchronized completion of a project’s activities, which reduces both time and cost. The proposed framework also incorporates procedures to resolve resource constraints at both the individual-resource and the crew levels as well. To address the lack of efficient repetitive-scheduling solutions, a new easy-to-use interactive scheduling tool has been developed to combine the benefits of CPM/LOB calculations with the introduced schedule improvements, along with new clearer visualizations of all schedule details (i.e., activities, units, crews etc.). The scheduling improvements proposed in this research and the developed scheduling tool prototype were validated on case studies and proved to greatly facilitate the efficient planning and delivery for repetitive infrastructure projects, which represent an increasing portion of construction business and are most challenging to execute

    A survey of variants and extensions of the resource-constrained project scheduling problem

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    The resource-constrained project scheduling problem (RCPSP) consists of activities that must be scheduled subject to precedence and resource constraints such that the makespan is minimized. It has become a well-known standard problem in the context of project scheduling which has attracted numerous researchers who developed both exact and heuristic scheduling procedures. However, it is a rather basic model with assumptions that are too restrictive for many practical applications. Consequently, various extensions of the basic RCPSP have been developed. This paper gives an overview over these extensions. The extensions are classified according to the structure of the RCPSP. We summarize generalizations of the activity concept, of the precedence relations and of the resource constraints. Alternative objectives and approaches for scheduling multiple projects are discussed as well. In addition to popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, the paper also provides a survey of many less known concepts. --project scheduling,modeling,resource constraints,temporal constraints,networks

    Comprehensive CP Optimization for Dynamic Scheduling in Construction

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    Delays and cost overruns are common facts in construction projects due to its increasing complexity, the day-to-day dynamic changes, the stricter execution constraints, and the general lack of efficient scheduling tools to support the optimization of construction plans. Currently, many scheduling tools and techniques are available, in addition to a large body of literature that focus on schedule optimization. Such tools and techniques, however, do not adequately represent or incorporate various practical decisions and constraints, nor provide the project manager with the ability to examine the combinations of actions in order to either plan or bring the project back within the constraints. This research enhances the schedule optimization research by efficiently modeling real-life decisions and constraints, and develops a framework to optimize planning and corrective-action decisions; dynamically before and during construction. The development of the proposed framework starts with a basic model that suits the schedule optimization decisions at the preconstruction stage. This model is then extended to a generic model that accommodates the dynamic schedule optimization needs during construction. The enhancements and extensions are formulated in a generic mathematical formulation to optimize the schedule’s decisions at any stage. This formulation integrates a wide range of scheduling options (e.g., linear crashing, activity multimodes, overlapping, and multipath networks), and incorporates the project manager’s preferences about the corrective-action decisions’ implementation. The formulation also considers a variety of practical constraints (e.g., variable resource availability, correlated modes, and intermediate milestones); and uses a multi-objective optimization to tradeoff among the project time, cost, resources, and permissible schedule changes during construction. Based on the mathematical formulation, the proposed framework was then coded using the advanced v constraint programming tool “IBM ILOG CPLEX Optimization Studio”. To validate the model, multiple experiments on four case studies were used to prove the functionality, practicality, and its better representation of real-life construction challenges. Two of these case studies are taken from the literature to prove the ability of the comprehensive model to achieve better solutions. Construction experts were also consulted at multiple stages of this work to investigate the relevance of the framework. Introducing the proposed framework as an add-on to standard project management software is expected to change the practitioners’ perception that optimization is a theoretical and complex tool. Therefore, it helps to present optimization as a useful decision support tool for construction scheduling

    Time-cost Trade-off Analysis for Highway Construction projects

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    The Construction industry, which can be in the form of residential building, commercial, public and utility buildings, or civil engineering building, has a huge influence on any nation\u27s economy. Its influence can be either manifested in its contribution to the economy or the service it provides to the community. In order to build any infrastructure project with a balanced cost, time, and quality, project managers search for alternatives that can satisfy these contradicting attributes. The traditional time-cost trade-off was enhanced with the three-dimensional time-cost- quality optimization in the last two decades. The optimization is aimed to minimize the time and cost as much as possible while increasing the quality of the infrastructure to be built. The issue of financing in developing countries has been a bottle neck of success in constructing infrastructure like highway. Many researchers have concluded in their studies the causes of time and cost overrun in high-way construction were, contractors\u27 financial problems, Inflation, progress payments delay by owner, political issues, variations, lack of managemental skills, cost fluctuation of materials during construction, environmental issues, Shortage in equipment, Inadequate contractor experience etc. The number of studies in the literature that deals with financial optimization and cash-flow analysis to address the problem of financing and inflation are getting more attention. The cash-flow analysis and maximum overdraft to be paid give a good indication to the main participants about the trends toward cost and time overrun. They can also help in making a proper decision right at the beginning. The purpose of this study is to deal with the optimization of time and profit of highway constructions taking in to consideration the amount of available credit and future value of the cost of each activity and cash-flow analysis in a comprehensive model. This type of analysis gives the contractor how its profit will be influenced with his allowable credits and the time associated with it. Besides, the model also generates a line of balance scheduling for the project as highways are among the repetitive projects. The cash-flow analysis gives extra information on the overdraft so that it can be optimized to find good combination of execution of the activities which will minimize the overdraft, interest paid to banks and most importantly maximize the profit to be gained by the project using GA approach. This type of analysis also gives alternatives for contractors how much profit would they like to gain by providing different amount of credits. At first the profit and time are optimized individually to get the maximum profit and minimum time for completing the project. Then the multi-objective optimization using goal programing takes place which tries to minimize the deviation from the optimum individual values by assigning importance weight to the individual objectives to find the near optimal solution. The model is tested for different allowable credits and its sensitivity analysis outcomes are plotted to see the relationship between the allowable credits and the profit. To validate the efficiency of the developed model, it is applied to a project from the literature that addresses scheduling and cost optimization of repetitive projects. It is found that the outcome of the model that maximizes the profit and minimizing the time outlooks the results of the literature with 4.65% and 0.38% improvement in duration and cost of the project respectively

    Robust Optimization for Integrated Construction Scheduling and Multiscale Resource Allocation

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    This research investigates an integrated problem of construction scheduling and resource allocation. Inspired by complex construction practices, multi-time scale resources are considered for different length of terms, such as permanent staff and temporary workers. Differing from the common stochastic optimization problems, the resource price is supposed to be an uncertain parameter of which probability distribution is unknown, but observed data is given. Hence, the problem here is called Data-Driven Construction Scheduling and Multiscale Resource Allocation Problem (DD-CS&MRAP). Based on likelihood robust optimization, a multiobjective programming is developed where project completion time and expected resource cost are minimized simultaneously. To solve the problem efficiently, a double-layer metaheuristic comprised of Multiple Objective Particle Swarm Optimization (MOPSO) and interior point method named MOPSO-interior point algorithm is designed. The new solution presentation scheme and decoding process are developed. Finally, a construction case is used to validate the proposed method. The experimental results indicate that the MOPSO-interior point algorithm can reduce resource cost and improve the efficiency of resource utilization
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