Time-cost Trade-off Analysis Research Articles

ANALYSIS OF PROJECT DELAY USING THE CRITICAL PATH METHOD (CPM): A CASE STUDY ON THE CONSTRUCTION PROJECT OF THE OPD OFFICE BUILDING IN PASURUAN

In construction project control, the main factors of concern are quality, time and cost control. So it is necessary to use one method in the implementation of control. This study aims to analyze the time and cost of the Raci OPD Office Building Construction project. The benefit of this research is to anticipate potential delays that occur in the project. The problem limitation is focused on work that has not been completed in the remaining time of the contract period. To analyze time and cost, this research uses Critical Path Method (CPM) and Time-Cost Trade-Off (TCTO) which begins with determining the work network and critical path. TCTO analysis is carried out by shortening the duration of work by adding 3 hours of overtime and calculating the Crash Slope of each job on the critical path. Rescheduling is done by accelerating the work that has the lowest cost. The results showed that the most effective rescheduling was carried out on the Lt.3 Installation and Plastering work with the acquisition of an acceleration duration of 8 days. And the total cost required for this acceleration is Rp. 29,441,424, - or Rp. 1,226,726, - per day for 24 days.

STUDY OF COST AND TIME ANALYSIS USING THE TIME COST TRADE-OFF (TCTO) METHOD IN THE CONSTRUCTION PROJECT OF THE OFFICE BUILDING OF A GOVERNMENT AGENCY (OPD) IN PASURUAN

In construction project control, the main factors of concern are quality, time and cost control. So it is necessary to use one method in the implementation of its control. This study aims to analyze the time and cost of the Raci OPD Office Building Construction project. The benefit of this research is to anticipate potential delays that occur in the project. The problem limitation is focused on work that has not been completed in the remaining time of the contract period. To analyze time and cost, this research uses Critical Path Method (CPM) and Time-Cost Trade- Off (TCTO) which begins with determining the work network and critical path. TCTO analysis is carried out by shortening the duration of work by adding 3 hours of overtime and calculating the Crash Slope of each job on the critical path. Rescheduling is done by accelerating the work that has the lowest cost The results showed that the most effective rescheduling was carried out on the Lt.3 Installation and Plastering work with the acquisition of an acceleration duration of 8 days. And the total cost required for this acceleration is Rp. 29,441,424, - or Rp. 1,226,726,- per day for 24 days.

TIME COST TRADE OFF ANALYSIS ON PROJECT ACCELERATION WITH ADDITIONAL WORKING HOURS (OVERTIME) (CASE STUDY: BUILDING REHABILITATION PROJECT ON DEKRANASDA HALL OF WEST KALIMANTAN)

Acceleration on projects is frequently used when there is a mismatch between the actual and planned schedules. In addition, acceleration is frequently implemented in response to requests from the project owner to complete the project as quickly as possible to meet specific goals so that the building can be used immediately. The owner of the Dekranasda Building and Hall in West Kalimantan requested that the project be finished immediately so that the Dekranasda Building could be used as the location for a national UMKM exhibition event. The initial plan for this project was scheduled for 152 working days. Because there would be an exhibition event, the project was accelerated to 128 working days. The purpose of this research is to accelerate the project for 24 days. The stages of this acceleration analysis start from finding what activities can be softened, then compiling a network diagram to identify activities on the critical path, followed by crashing analysis to get crash duration, crash cost, and cost slope, then Time Cost Trade-Off analysis is carried out. This research uses the PDM (Precedence Diagram Method) method applied to Microsoft Project to compile a Network Diagram. The results of the acceleration analysis show that the crashing process is carried out until the 12th crashing to meet the target acceleration duration of 128 working days from the normal duration of 152 working days, and the usual 24-day length is shortened. Twelve tasks have been added, raising the overall project cost from Rp. 6,794,007,874 to Rp. 7,091,725,614 by a total of Rp. 297,717,741.

Solving Time-Cost Tradeoff Problem with Resource Constraint Using Fuzzy Mathematical Model

Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy theory combining CPM computations, time-cost trade off analysis and resource constraint. MATLAB software has been adopted to perform ranking process, for each case, that facilitates obtaining the optimum solution. This research infers that it is possible to perform time-cost trade off analysis with resource restriction simultaneously, which ensures achieving scheduling optimum solution reducing the effort and the time when performing these techniques in succession using traditional methods.

Practical Tool for Development of Non-Dominated Optimum Front in Time–Cost Trade-off analysis

Practical Tool for Development of Non-Dominated Optimum Front in Time–Cost Trade-off analysis

Analysis of Time Comparison and Costs of Implementing Road Implementation with Time Cost Trade-Off Method

Project for the construction of the Gunungsari Banjar Sugihan - Kandangan diversion channel, Surabaya, in the implementation of this project there was a delay in how many works. One way to anticipate this delay is by accelerating it using the Time Cost Tread Off method, through alternative working hours (overtime) and additional labor. The method is used so that the project can run smoothly and so that the project can be accelerated in completion. Time-Cost Trade-Off analysis, better known as TCTO. jobs included in the critical cross and jobs that are not allowed to delay are as follows: Urugan Sirtu (solid), Lean concrete fc 10 Mpa work, Rigid pavement fc 30 Mpa work finishing growing, iron beginning work.

Time-cost trade-off analysis of a priority based assignment problem

In this paper, a bi-objective priority based assignment problem (BPBAP) related to an industrial project, is considered in which, depending upon the work breakdown structure, the n tasks involved in the project are divided into two categories. One of the categories consists of m primary tasks and the other one consists of $$(n-m)$$ secondary tasks (for $$m<n$$ ). The project is such that the secondary tasks can be executed only after the primary tasks are finished, however, the tasks within each category may be executed simultaneously. This problem is a special case of categorized assignment scheduling problem, discussed extensively in literature. The BPBAP is studied with the objective of minimizing simultaneously, the two criteria namely, total execution time and total assignment cost of the project which are equal to the sum of execution times and assignment costs respectively, of primary and secondary tasks. Generally, it is not possible to optimize both the objectives simultaneously, therefore, there is a need to do time-cost trade-off analysis of the problem. Since, the present problem is based on two-stage execution of the project (one stage for each category of tasks), therefore, a criteria based iterative algorithm considering all the possible combinations of the parameters of both the categories, is developed that finds all the non-dominated points of BPBAP in a polynomial time. Numerical illustrations are provided in the support of theory.

İnşaat Projelerinde Zaman Maliyet Ödünleşim Problemi: Örnek Olay Analizi

Globalleşen dünyada artan rekabet koşullarıyla birlikte inşaat projelerinin gerek zaman gerekse maliyet olarak optimize edilmesi kaçınılmaz bir hal almıştır. Bu ortamda proje yöneticisinin karşı karşıya olduğu en önemli zorluklardan biri, projeye ayrılan zaman ve finansal kaynak kısıtları içerisinde istenilen kalite standartlarına göre projenin yapılabilirliğine karar vermek ve sonrasında tamamlanmasını sağlamaktır. Günümüzde proje yöneticileri sürekli bir zaman ve maliyet indirgenmesi baskısıyla karşı karşıyadır. Bu noktada her bir proje için zaman ve maliyet ödünleşiminin nasıl yapılacağı ve hangi türden bir model geliştirileceği proje yöneticilerinin üzerinde çalıştığı en ciddi problemlerden birisi olarak karşımıza çıkar. Bu çalışmanın amacı örnek olarak ele alınan proje üzerinde zaman-maliyet ödünleşim analizi ile proje süresinin nasıl indirgendiğini göstermektir. Çalışmada İlk olarak hızlandırma sürelerini ve maliyetlerini bulmak için sezgisel bir yöntem olan kritik yol yöntemi (CPM) kullanılarak kritik yol ve bu yol üzerindeki kritik aktiviteler belirlenmiştir. Projede yer alan faaliyetlerin sürelerinin deterministik olduğu öngörülmüştür. Kritik yol üzerindeki faaliyetlerin hızlandırma süreleri sezgisel yöntemle tespit edildikten sonra amaç fonksiyonun belirlenmesi için bu faaliyetlerin maliyet eğimi hesaplanmıştır. Optimizasyon modeli oluşturarak zaman ve maliyet parametreleri arasındaki ilişkiyi tanımlayabilmek için regresyon analizi uygulanmış ve oluşturulan problem MATLAB 9,7 programı ile çözülmüştür. Analiz sonucunda projenin en uygun 741 lira bütçe ve 2 hafta hızlandırmayla toplam 17 haftada tamamlanabileceği görülmüştür.

Optimizing time–cost in generalized construction projects using multiple-objective social group optimization and multi-criteria decision-making methods

PurposeProject managers work to ensure successful project completion within the shortest period and at the lowest cost. One of the main tasks of a project manager in the planning phase is to generate the project time–cost curve, and furthermore, to determine the most appropriate schedule for the construction process. Numerous existing time–cost tradeoff analysis models have focused on solving a simple project representation without regarding for typical activity and project characteristics. This study aims to present a novel approach called “multiple-objective social group optimization” (MOSGO) for optimizing time–cost decisions in generalized construction projects.Design/methodology/approachIn this paper, a novel MOGSO to mimic the time–cost tradeoff problem in generalized construction projects is proposed. The MOSGO has slightly modified the mechanism operation from the original algorithm to be a free-parameter algorithm and to enhance the exploring and exploiting balance in an optimization algorithm. The evidential reasoning technique is used to rank the global optimal obtained non-dominated solutions to help decision makers reach a single compromise solution.FindingsTwo case studies of real construction projects were investigated and the performance of MOSGO was compared to those of widely considered multiple-objective evolutionary algorithms. The comparison results indicated that the MOSGO approach is a powerful, efficient and effective tool in finding the time–cost curve. In addition, the multi-criteria decision-making approaches were applied to identify the best schedule for project implementation.Research limitations/implicationsAccordingly, the first major practical contribution of the present research is that it provides a tool for handling real-world construction projects by considering all types of construction project. The second important implication of this study derives from research finding on the hybridization multiple-objective and multi-criteria techniques to help project managers in facilitating the time–cost tradeoff (TCT) problems easily. The third implication stems from the wide-range application of the proposed model TCT.Practical implicationsThe model can be used in early stages of the construction process to help project managers in selecting an appropriate plan for whole project lifecycle.Social implicationsThe proposal model can be applied to multi-objective contexts in diversified fields. Moreover, the model is also a useful reference for future research.Originality/valueThis paper makes contributions to extant literature by: introducing a method for making TCT models applicable to actual projects by considering general activity precedence relations; developing a novel MOSGO algorithm to solving TCT problems in multi-objective context by a single simulation; and facilitating the TCT problems to project managers by using multi-criteria decision-making approaches.

Multi-objective optimization of time-cost-quality in construction projects using genetic algorithm

In this study, it was aimed to develop a model that provides Time-Cost-Quality optimization in construction projects using Genetic algorithm method. In order to fulfill that, Matlab codes for a multi-purpose genetic algorithm that performs Time-Cost-Quality optimization were developed and applied to the problem, and the targeted success level was substantially achieved. This model is capable of performing and visualizing an advanced three-dimensional time, cost, quality tradeoff analysis instead of the traditional two-dimensional time-cost tradeoff analysis. It was possible to select the desired alternative under the project conditions obtaining pareto images called a set of solutions rather than a single solution. In addition, one of the main objectives of this study is to develop an effective model to assist the main contractors of the construction in selecting the most suitable subcontractors.

Developing an optimization financing cost-scheduling trade-off model in construction project

Time-cost trade-off analysis is one of the most challenging tasks of construction project planners. Project planners face complicated multivariate time-cost optimization problems that require simultaneous minimization of total project duration and total project cost while considering issues related to the optimal present value of profit. In addition, given the complexity of construction projects in recent years, clever management has become increasingly important in cases of project financing and scheduling. There are choices and limits that make it difficult for project planners to develop a proper financing plan considering project time status. Therefore, the methods of financing affect the project plan. Parameters such as interest rate, contract terms, and financing options (i.e., types of the loan) in the project construction period can change the final profit value of the project. Hence, a skilled planner should consider various effective parameters for scheduling projects. This study presents a hybrid meta-heuristic algorithm to solve a multi-objective optimization problem in construction project planning and financing. The main objective of the model is to present a Pareto chart that shows the trade-off between duration of the project and the financing cost by considering different durations for each activity of the project and various financing options. The model is first validated in a simple case study and then applied to a large-scale case study. The model shows the optimal solutions which have time and financing cost. For each optimal solution, the model will create a cash flow containing project (direct and indirect cost and payments) and financing flows (borrowed money and repayments of principal and interest) based on a work schedule. Finally, a sensitivity analysis is performed to examine the effects of changes in the various parameters of the project cash flow on the ultimate results. It is shown that the proposed model is superior to the existing models in finding better project planning solutions with lower total project duration and lower total project financing cost in the proposed construction project financing problems. In addition, the proposed model improves the solutions through generations and provides optimal solutions in acceptable processing time.

Maximizing expected contractor profit using an integrated model

PurposePlanning for increased contractor profits should start at the time the contract is signed because low profits and lack of profitability are the primary causes of contractor failure. The purpose of this paper is to propose an integrated profit maximization model (IPMM) that aims for maximum expected profit by using time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration. This kind of integrated approach was never researched in the past.Design/methodology/approachIPMM is programmed into an automated system using MATLAB 2016a. It generates an optimal work schedule that leads to maximum profit by means of time-cost tradeoff analysis considering different activity acceleration/deceleration methods and adjusting the start/finish times of activities. While doing so, IPMM minimizes the contractor’s financing cost by considering combinations of different financing alternatives such as short-term loans, long-term loans and lines of credit. IPMM also considers the impact of extending the project duration on project profit.FindingsIPMM is tested for different project durations, for the optimality of the solutions, differing activity start/finish times and project financing alternatives. In all cases, contractors can achieve maximum profit by using IPMM.Research limitations/implicationsIPMM considers a deterministic project schedule, whereas stochastic time-cost tradeoff analysis can improve its performance. Resource allocation and resource leveling are not considered in IPMM, but can be incorporated into the model in future research. Finally, the long computational time is a challenge that needs to be overcome in future research.Practical implicationsIPMM is likely to increase profits and improve the chances of contractors to survive and grow compared to their competitors. The practical value of IPMM is that any contractor can and should use IPMM since all the data required to run IPMM is available to the contractor at the time the contract is signed. The contractor who provides information about network logic, schedule data, cost data, contractual terms, and available financing alternatives and their APRs can use an automated IPMM that adjusts activity start times and durations, minimizes financing cost, eliminates or minimizes time extensions, minimizes total cost and maximizes expected profit.Originality/valueUnlike any prior study that looks into contractors’ profits by considering the impact of only one or two factors at a time, this study presents an IPMM that considers all major factors that affect profits, namely, time-cost tradeoff analysis, adjusted start times of activities, minimized financing cost and minimized extension of work schedule beyond the contract duration.

Time-cost tradeoff analysis with minimized project financing cost

Abstract Time-cost tradeoff analysis allows a contractor to build a project using an optimal schedule that leads to minimum cost. The financing cost can be minimized if the financing decision considers different financing alternatives such as short-term and long-term loans and lines of credit. Financing optimization should be integrated into time-cost tradeoff analysis to minimize total cost and maximize profit. This study proposes an integrated model that performs time-cost tradeoff analysis and financing optimization. A hybrid GALP algorithm is introduced to solve the optimization by combining genetic algorithms (GA) and linear programming (LP). The proposed model is tested using small and large networks: (1) to prove that optimal results are obtained in terms of the financing cost and profit if the proposed integrated model is used, (2) to validate the performance and structure of each model, and (3) to confirm the practicality of the proposed models in large networks.

Strategy management of construction workspaces by conflict resolution algorithm and visualization model

PurposeThe spatial conflicts and congestion of construction resources are challenges that lead to the reduction in efficiency. The purpose of this paper is to enable users to detect and resolve workspace conflicts by implementing four resolution strategies in a five-dimensional (5D) CAD model. In addition to resolving conflicts, the model should be able to optimize time and cost of the projects. In other words, three variables of spatial conflicts, time and cost of project are considered simultaneously in the proposed model to find the optimum solution.Design/methodology/approachIn the first step, a 5D simulation model is developed that includes time, cost and geometrical information of a project. Then, time-cost trade-off analysis was carried out to distinguish optimum schedule. The schedule was imported to the 5D CAD model to detect spatial conflicts. Finally, a novel algorithm was implemented to solve identified conflicts while imposing minimum project’s time and cost. Several iterations are performed to resolve all clashes using conflict resolution algorithm and visual simulation model.FindingsThe proposed methodology in this research was applied to a real case. Results showed that in comparison to the normal and initial schedule with 19 conflicts, the finalized schedule has no conflict, while time and cost of the project are both reduced.Research limitations/implicationsImplementing the proposed methodology in construction projects requires proper technical basis in this field. In this regard, the executive user should have a proper understanding of the principles, concepts and tools of building information modeling and have project management knowledge. Also, the implementation conditions of the basic model requires the determination of the construction methods, estimated volumes of working items, scheduling and technical specification. The designed methodology also has two limitations regarding to its implementation. The first is the fact that strategies should be applied manually to the schedule. The other one pertains to the number of strategies used in the research. Four strategies have been used in the conflict resolution algorithm directly and the two others (spatial divisibility and activities breakdown strategies) have been used as default strategies in the visual simulation model. Since the unused strategies including the changing of construction method and the activity resources are subjective and depend upon the planner and project manager’s personal opinion, the authors have avoided using them in this research.Practical implicationsThe method proposed in this research contributes the coordination of the working teams at the planning and execution phases of the project. In fact, the best location and work direction for each working team is presented as a schedule, so that the space conflict may not come about and the cost can be minimized. This visual simulation not only deepens the planners’ views about the executive barriers and the spatial conditions of the worksite, it also makes the construction engineers familiar on a daily basis with their executive scope. Therefore, it considerably improves the interactions and communication of the planning and construction teams. Another advantage and application of this methodology is the use of initial and available projects’ documents including the schedule and two-dimensional drawings. The integration of these basic documents in this methodology helps identify the spatial conflicts efficiently. To achieve this, the use of the existing and widely-used construction tools has facilitated the implementation of the methodology. Using this system, planners have applied the strategies in an order of priority and can observe the results of each strategy visually and numerically in terms of time, cost and conflicts. This methodology by providing the effective resolution strategies guides the practitioner to remove conflicts while optimum time and cost are imposed to project.Originality/valueContrary to the previous models that ignore cost, the proposed model is a 5D visual simulation model, which considers the variable of cost as a main factor for conflict identification and resolution. Moreover, a forward-pass approach is introduced to implement resolution strategies that are novel compared to other investigations.

Exact Time–Cost Tradeoff Analysis in Concurrency-Based Scheduling

AbstractA construction project can be accelerated by overlapping critical activities. This paper presents a computational method called exact time–cost tradeoff (ETCT) in concurrency-based scheduling that identifies exact global overlaps between critical activities. It calculates the rework cost slope and amount by integrating the activities’ concurrency attributes, identifies the exact global solution, and computes the probability to complete a project within the project completion time (PCT) and/or the project completion cost (PCC). The study is of value to project schedulers because ETCT identifies the exact global solution (i.e., the set of activities to be overlapped and the exact overlap rates between these activities) expeditiously, and establishes a compressed schedule that satisfies a project’s budget and duration constraints. This is also relevant to researchers in that it clearly defines the computational formula to compute the exact solution in detail and facilitates a comparison of the outcom...

Mixed-integer nonlinear programming based optimal time scheduling of construction projects under nonconvex costs

Optimal project scheduling under nonconvex time-cost relations represents a challenging problem in construction management. The nonconvex time-cost relations may appear in a construction project when several different duration options are available for its activities due to alternative technological processes enabled for their realization or wide accessibility of production resources. The source of nonconvexity of the project scheduling optimization problem can also be the project penalty- or bonus-duration relations arranged within the construction contract. The aim of this paper is to present the mixed-integer nonlinear programming (MINLP) based optimal time scheduling of construction projects under nonconvex costs. For this purpose, the MINLP model was developed and applied. A numerical example from literature and an example of construction project time-cost trade-off analysis under practical nonconvex penalty function are given in the paper to demonstrate advantages of MINLP optimization. The example from literature first presented the capability of the MINLP approach to obtain the optimal solution for difficult, highly combinatorial nonconvex discrete project scheduling problem. Thereupon, the following example revealed that the optimal project time-cost curve may take very nonuniform shape on account of discrete nature of activity direct cost options and nonconvex relation between project duration and total cost. In this way, the presented study intends to provide practitioners with new information from the field of optimization techniques for project scheduling as well as an alternative view on performance of total cost when project duration is changed.

An evolutionary optimization method to determine optimum degree of activity accelerating and overlapping in schedule compression

Compressing project schedule using activity accelerating and overlapping requires that an intensive time–cost trade-off analysis be carried out, to determine costs and benefits for each day of compression. However, the cost elements and implications of compression techniques differ significantly, since activity accelerating imposes extra direct cost whereas activity overlapping adds a risk of changes and rework. Such a trade-off becomes even more complicated in capital projects comprised of a large number of schedule activities and relationships. The variety of combinations of accelerating and overlapping of different activities in these complex networks can offer numerous possibilities for compression with various costs and potential risks. The lack of a reliable analytical tool for performing a precise cost-benefit analysis causes this critical task to be performed in a subjective manner during the planning stage of projects. The purpose of this paper is to present an advanced method using a multi-objective evolutionary optimization tool seeking the optimum degree of accelerating and overlapping during the schedule compression process. This optimization technique would be beneficial in maximizing project benefits while meeting the intended target dates.

A model for scheduling projects under the condition of inflation and under penalty and reward arrangements

A zero-one mixed integer linear programming model is developed for the scheduling of projects under the condition of inflation and under penalty and reward arrangements. The effects of inflation on time-cost trade-off curves are illustrated and a modified approach to time-cost trade-off analysis presented. Numerical examples are given to illustrate the model and its properties. The examples show that misleading schedules and inaccurate project-cost estimates will be produced if the inflation factor is neglected in an environment of high inflation. They also show that award of penalty or bonus is a catalyst for early completion of a project, just as it can be expected.

Project schedule compression: a multi-objective methodology

Purpose – This paper aims to present a new method to circumvent the limitations of current schedule compression methods which reduce schedule crashing to the traditional time-cost trade-off analysis, where only cost is considered. Design/methodology/approach – The schedule compression process is modeled as a multi-attributed decision making problem in which different factors contribute to priority setting for activity crashing. For this purpose, a modified format of the Multiple Binary Decision Method (MBDM) along with iterative crashing process is utilized. The method is implemented in MATLAB, with a dynamic link to MS-Project to facilitate the needed iterative rescheduling. To demonstrate the use of the developed method and to present its capabilities, a numerical example drawn from literature was analysed. Findings – When considering cost only, the generated results were in good agreement with those generated using the harmony search (HS) method, particularly in capturing the project least-cost duratio...

Accuracy of the Kaufmann and Desbazeille Algorithm for Time-Cost Trade-off Project Problems

The time-cost tradeoff analysis is a very important issue in the project management. The Kaufmann- Desbazeille method is considered by numerous authors as an exact algorithm to solve that problem, but in some articles it has been proved that for specifi c network cases the procedure only leads to quasi-optimal solutions. In this paper we calculate the average accuracy of the algorithm for several deterministic and randomly generated networks. The accuracy of the KDA is the worst when: the network is generated in a deterministic way (an even number of nodes, the network contains only arcs connecting neighbouring nodes, neighbouring even nodes and neighbouring odd nodes, thus it has many critical and subcritical paths with a lot of common arcs), each type of activities in such a network has very specific time-cost characteristics. The structure of the network has the infl uence on the performance of KDA. It should be however analyzed together with the distribution of the shortening costs.