Journal of Industrial and Systems Engineering
Volume:12 Issue: 1, Winter 2019

One of the important problems in the field of Construction Industry is ‘rework’. It affects time, costs, quality, and almost every criteria of project success. As a result of rework and ineffective use of resources and materials in the workshops, there is always a considerable loss of resources, materials, investments, and workforce-time. Designing and planning through full awareness of clients and stakeholders, effective communication between the project factors, utilizing quality management systems, and using Information Technology [IT], can lead to a reduction of rework. In the recent years because of, the global development of IT, and widespread use of BIM-which coordinates all of the software and sections of the construction-the emergence of errors and inconsistencies have been dramatically decreased; helping the experts to realize their full professional potential in [doing] the projects. This study, while analyzing the effects of rework and its related factors on the civil projects, expresses the need for implementing TQM system through BIM tool, and finally provides a model for TQM implementation through using of BIM.

Resource constrained project scheduling problem is one of the most important issues in project planning and management. The objective function of this problem is to minimize the completion time of a project. When there is budget constraint or high risk for investment, using the criteria such as cash flows is so important. The development of computer systems and processors makes it possible to take more assumptions into modeling to obtain robust optimal solution. Recent research has been conducted on multimode resource constrained project scheduling problem with preemptive activities (P-MRCPSP). Assuming preemption of activities causes the model to approach the real-world problems in project scheduling. This assumption may occur due to factors such as equipment failure and shortage of resources. In most of the previous studies, the change in mode of activities was not possible after the discontinuation. In this paper, it is assumed that each activity can continue in various modes of operation after a stop. The developed model aims to minimize project completion time and maximize cash flow of the project, simultaneously. Two algorithms, i.e. Simulated Annealing (SA) and Multiple Objective Particle Swarm Optimization (MOPSO) have been developed to solve the proposed model. The obtained results of these two algorithms show that SA algorithm has the better performance.

The resource-constrained project scheduling problem is to find a schedule that minimizes the project duration subject to precedence relations and resource constraints. To further account for economic aspects of the project, one may add an objective of cash nature to the problem. In addition, dynamic nature and variations in real world are known to introduce uncertainties into data. Therefore, this study is aimed at proposing a multi-objective model for resource-constrained project scheduling problem, with the model objectives being to minimize makespan, and maximize net present value of the project cash flows; the proposed model has activity times expressed in fuzzy numbers where the corresponding uncertainties are taken into account. The project environment is considered to be a multi-resource environment where more than one resource is needed for the execution of any activity. Also, the proposed model comes with time lags in precedence relations between activities. The proposed model is validated by using epsilon-constraint method. The α-cut approach as well as the expression of acceptable risk level by the project manager is used to defuzzificate fuzzy activity durations. Since the problem is NP-hard, a NSGA-II meta-heuristic algorithm is proposed to solve the problem. The algorithm performance has been evaluated in terms of different criteria.

This paper proposes a new mixed-integer model for the multi-skill resource-constrained project scheduling problem (MSRCPSP). The interactions between workers are represented as undirected networks. Therefore, for each required skill, an undirected network is formed which shows the relations of human resources. In this paper, community detection in networks is used to find the most compatible working groups to perform project activities. In this respect, a greedy algorithm (GRA) is proposed to detect the most compatible communities of workers. The proposed greedy algorithm maximizes modularity as a well-known objective to find high-quality communities of workers. Besides, a new heuristic is developed to assign workers to activities based on the communities obtained by the GRA. The MSRCPSP is an NP-hard optimization problem with the objective of minimizing the makespan of the project. Therefore, a dandelion algorithm (DA), which is a meta-heuristic, is proposed to solve the problem. The dandelion algorithm is used to solve test problems of the iMOPSE</em> dataset. To validate the outputs of the proposed method, three other meta-heuristics including genetic algorithm (GA), harmony search (HS) algorithm, and differential evolution (DE) method are employed. The Taguchi method is hired to tune all algorithms. These algorithms are compared with each other in terms of several performance measures. The results show the superiority of the dandelion algorithm in terms of all performance measures.

Macroeconomic investment at the corporate level has grown rapidly in recent years. Given that the resources of the organization are usually less than the number of projects ahead in the organization, selecting projects from a portfolio of projects and making decisions in this regard is inevitable in the organization. Choosing the wrong one will have many negative consequences, including wasting resources in the organization. It also destroys resources within the organization that, if used correctly in a more appropriate project, will have benefits for the organization. In recent years, due to some problems, the country's economic markets have fluctuated. These fluctuations are largely unpredictable in nature, which have a significant negative impact on economic and investment organizations. Given this need, the current research is attempting to provide a solution to best balance project portfolio in uncertain terms. Therefore, this paper has proposed a model for project balancing under uncertainty conditions considering resilience factors in crisis, as stated, to prevent some projects from continuing if necessary. 4 scenarios are defined and a stochastic programming is implemented. So far, the concept of project portfolio balancing and modeling has rarely been addressed. Most of the time, a financial portfolio is presented and a balancing model is provided for it, especially in the field of equity, or generally, taking into account indicators such as risk, prioritizing projects and providing a conceptual model to apply.