Optimizing time, cost and quality in multi-mode resource-constrained project scheduling
02 Jan 2019-Vol. 9, Iss: 1, pp 44-63
TL;DR: A framework to optimize time, cost and quality in a multi-mode resource-constrained project scheduling environment using Pareto optimal solutions is developed and good compromise solutions are obtained through multi-objective optimization.
Abstract: The purpose of this paper is to develop a framework to optimize time, cost and quality in a multi-mode resource-constrained project scheduling environment.,A case study approach identified the activity execution modes in building construction projects in India to support multi-mode resource-constrained project scheduling. The data required to compute time, cost and quality of each activity are compiled from real construction projects. A binary integer-programming model has been developed to perform multi-objective optimization and identify Pareto optimal solutions. The RR-PARETO3 algorithm was used to identify the best compromise trade-off solutions. The effectiveness of the proposed framework is demonstrated through sample case study projects.,Results show that good compromise solutions are obtained through multi-objective optimization of time, cost and quality.,Case study data sets were collected only from eight building construction projects in India.,It is feasible to adopt multi-objective optimization in practical construction projects using time, cost and quality as the objectives; Pareto surfaces help to quantify relationships among time, cost and quality. It is shown that cost can be reduced by increasing the duration, and quality can be improved only by increasing the cost.,The use of different activity execution modes compiled from multiple projects in optimization is illustrated, and good compromise solutions for the multi-mode resource-constrained project scheduling problems using multi-objective optimization are identified.
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TL;DR: The findings show that the use of the efficient execution mode in each activity leads to an optimal trade-off between the four project objectives, and can assist project managers with choosing the most appropriate execution modes for the activities to ultimately accomplish the project with the lowest time, cost and environmental impacts along with the highest quality.
Abstract: The purpose of this paper is to evaluate project activities' efficiency in different execution modes for the optimization of time–cost-quality and environmental impacts trade-off problem.,This paper presents a parallel Data Envelopment Analysis (DEA) method for evaluation of project activities with different execution modes to select the best execution mode and find a trade-off between objectives. Also, according to the nature of the project activities, outputs are categorized into desirable (quality) and undesirable (time, cost and environmental impacts) and analyzed based on the DEA model. In order to rank efficient execution modes, the ideal and anti-ideal virtual units method is used. The proposed model is implemented on a real case of a rural water supply construction project to demonstrate its validity.,The findings show that the use of the efficient execution mode in each activity leads to an optimal trade-off between the four project objectives (time, cost, quality and environmental impacts).,This study help project managers and practitioners with choosing the most efficient execution modes of project activities taking time–cost-quality-environmental impacts into account.,In this paper, in addition to time and cost optimization of construction projects, quality factors and environmental impacts are considered. Further to the authors' knowledge, there is no method for evaluating project activities' efficiency. The efficiency of different activity modes is also evaluated for the first time to select the most efficient modes. This research can assist project managers with choosing the most appropriate execution modes for the activities to ultimately accomplish the project with the lowest time, cost and environmental impacts along with the highest quality.
22 citations
TL;DR: The authors make full use of historical project data from the perspective of both quality and schedule management, and provide a novel method to intelligently and objectively analyze the relationship between quality risk and scheduling.
Abstract: The purpose of this paper is to mine information on the construction process of previous projects to develop a construction plan that meets both quality requirements and schedule constraints.,This paper uses a failure mode and effect analysis to evaluate the construction quality of 311 apartments in Shanghai. The authors also evaluate construction-scheduling control using the earned value management technique and implement an artificial neural network to correlate the results. The authors then develop a quality risk and schedule correlation model based on Big Data. The model can predict the relationship between the planned schedule and the project quality risk using multiple variables such as the number of layers, the schedule performance index and budget costs.,The methodology offers an innovative approach for assessment on the relationship between quality risk and project schedule. The authors have also built a multiple regression analysis model for comparative purposes with the model. The results show that the proposed model can better describe the relationship. The model can provide a quantitative quality risk value that changes with the planned schedule, as well as help project managers to understand the relationship between quality risk and project scheduling more accurately.,The research approach only focuses on quality risk under the impact of scheduling. Future efforts might focus on developing a model that connects failure models with project schedules and costs in order to improve the effort of quality management.,The model based on Big Data in this paper is developed using real projects and reflects the relationship between project quality risk and scheduling in real environments. The created application provides support for project managers to develop and adjust quality plans and schedules, thereby reducing deviations in quality and scheduling objectives.,The authors make full use of historical project data from the perspective of both quality and schedule management, and provide a novel method to intelligently and objectively analyze the relationship between quality risk and scheduling.
18 citations
TL;DR: In this paper, the authors compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment: the single-project approach (portfolio optimization) and the multiannual approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).
Abstract: Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).,A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India.,Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution.,It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified.,An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.
13 citations
TL;DR: The proposed method may allow for better use of the existing production potential of construction enterprises and ensure synchronization of the crews employed during the work, especially in the case of difficulties in acquiring qualified staff in construction industry.
Abstract: Abstract One of the key problems in managing the realization of a construction project is the selection of appropriate working crews and coordinating their activities in a way that ensures the highest degree of implementation of defined goals (minimizing the project duration and/or reducing downtime and related costs). Most of the existing methods of work harmonization used in construction industry allow obtaining the desired results only in relation to the organization of the processes realization in repetitive linear projects. In case of realization of non-linear construction objects or construction units, it is usually necessary to choose between the reduction of the project implementation time and maintaining the continuity of crews work on the units. It was found that there is a lack in the literature of developed method enabling harmonization of crews’ work, while minimizing the downtime at work and the duration of the entire project taking into account additional constraints, e.g. the need to not exceed the deadlines for the realization of the project stages. The article presents the concept of a multi-criteria optimization method of harmonizing the execution of non-linear processes of a multi-unit construction project in deterministic conditions. It will enable the reduction of realization time and downtimes in work, taking into account the preferences of the decision maker regarding the relevance of the optimization criteria. A mathematical model for optimizing the selection of crews and order of completion of units in multi-unit construction projects was also developed. In order to present the possibility of usage of the developed concept, an example of the optimal selection of crews and their work schedule was solved and presented. The proposed method may allow for better use of the existing production potential of construction enterprises and ensure synchronization of the crews employed during the work, especially in the case of difficulties in acquiring qualified staff in construction industry.
10 citations
Cites background from "Optimizing time, cost and quality i..."
...Due to the nonlinear nature of the discussed relation, in the model it was replaced by additional linear relations (17) - (19) (see Table 2), which allowed to maintain the linear character of the model....
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...sjk + Djk < sjl , j ∈ V , ∀ k, l : k, l ∈ L ∧ l = k + 1 (18) Condition for the completion of the units on objects in a xed order suk + Duk ≤ svl + M · (1 − yuv) + M · (2 − xur − xvr), ∀ (u, v) ∈ Jr , ∀r ∈ R, ∀k, l ∈ L (19) Allow setting deadlines for starting activity that cannot be carried out in parallel by the same contractor...
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...…in world literature (Mattila and Abraham, 1998; Kolisch and Padman, 2001; Herroelen and Leus, 2005; Kim et al., 2005; Anagnostopoulos and Koulinas, 2010; Jaśkowski and Sobotka, 2012; Benjaoran et al., 2015; Biruk and Jaśkowski, 2017; Kassandra and Suhartono, 2018; Kannimuthu et al., 2018)....
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TL;DR: The publication focuses on the views and needs of construction site engineering staff regarding methods of work organization, the need to reduce downtimes in the work of crews, the deadline for project realization and the selection of crews for tasks.
Abstract: In the literature on the scheduling of construction projects it is difficult to find a justification for adopting the criteria for evaluating work schedules based explicitly on the preferences of those who develop them. This article tries to fill this gap and provide information on the preferences of construction site managers for sustainable scheduling and organization of construction projects. The publication focuses on the views and needs of construction site engineering staff regarding methods of work organization, the need to reduce downtimes in the work of crews, the deadline for project realization and the selection of crews for tasks. This information was obtained on the basis of surveys conducted among managerial staff of various levels (74 people). The authors hope that the information provided in this publication will allow the creation of more reliable tools to support construction managers better adapted to their preferences and needs, and therefore more likely to be applied in practice.
5 citations
References
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TL;DR: An overview over various extensions of the basic RCPSP, including popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, is given.
Abstract: 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.
856 citations
TL;DR: An algorithm based on the principles of GAs for construction time-cost trade-off optimization and a computer program that can execute the algorithm efficiently are presented.
Abstract: Time-cost trade-off analysis is one of the most important aspects of construction project planning and control. There are trade-offs between time and cost to complete the activities of a project; in general, the less expensive the resources used, the longer it takes to complete an activity. Using critical path method (CPM), the overall project cost can be reduced by using less expensive resources for noncritical activities without impacting the project duration. Existing methods for time-cost trade-off analysis focus on using heuristics or mathematical programming. These methods, however, are not efficient enough to solve large-scale CPM networks (hundreds of activities or more). Analogous to natural selection and genetics in reproduction, genetic algorithms (GAs) have been successfully adopted to solve many science and engineering problems and have proven to be an efficient means for searching optimal solutions in a large problem domain. This paper presents: (1) an algorithm based on the principles of GAs for construction time-cost trade-off optimization; and (2) a computer program that can execute the algorithm efficiently.
441 citations
TL;DR: In this paper, improvements are proposed to resource allocation and leveling heuristics, and the GA technique is used to search for near-optimum solution, considering both aspects simultaneously.
Abstract: Resource allocation and leveling are among the top challenges in project management. Due to the complexity of projects, resource allocation and leveling have been dealt with as two distinct subproblems solved mainly using heuristic procedures that cannot guarantee optimum solutions. In this paper, improvements are proposed to resource allocation and leveling heuristics, and the Genetic Algorithms (GAs) technique is used to search for near-optimum solution, considering both aspects simultaneously. In the improved heuristics, random priorities are introduced into selected tasks and their impact on the schedule is monitored. The GA procedure then searches for an optimum set of tasks' priorities that produces shorter project duration and better-leveled resource profiles. One major advantage of the procedure is its simple applicability within commercial project management software systems to improve their performance. With a widely used system as an example, a macro program is written to automate the GA proced...
374 citations
TL;DR: This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem based on random keys that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm.
Abstract: This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.
341 citations
TL;DR: In this article, a multi-objective optimization model that supports decision makers in performing this challenging task is presented. The model is designed to transform the traditional two-dimensional time-cost tradeoff analysis to an advanced three-dimensional quality trade-off analysis.
Abstract: Many departments of transportation have recently started to utilize innovative contracting methods that provide new incentives for improving construction quality. These emerging contracts place an increasing pressure on decision makers in the construction industry to search for an optimal resource utilization plan that minimizes construction cost and time while maximizing its quality. This paper presents a multiobjective optimization model that supports decision makers in performing this challenging task. The model is designed to transform the traditional two-dimensional time-cost tradeoff analysis to an advanced three-dimensional time-cost-quality trade-off analysis. The model is developed as a multiobjective genetic algorithm to provide the capability of quantifying and considering quality in construction optimization. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in generating and visualizing optimal tradeoffs among construction time, cost, and quality.
279 citations