Resource-Constrained Project and Multi-Project Scheduling Problems (RCPSPs and RCMPSPs) have been essential topics of study over the last three decades. Both prob-lems consist of activities that must be scheduled subject to precedence and resource constraints. This paper surveys studies of RCPSPs and RCMPSPs under consideration of four categories of project activities, simply recorded as categories A, B, C, and D. Category A refers to activities can be performed using fixed resources along The Y-axis over fixed durations along The X-axis, and cannot be interrupted. Category B applies to activities that can be performed using the same type of resource in category A but can be interrupted. Category C refers to activities that can be performed using flexible resources over flexible durations and cannot be interrupted. Category D refers to activities can be performed using flexible resources over flexible durations and can be interrupted. Many algorithms have been developed to solve the RCPSPs and RCMPSPs when activities are classified individually under category A, B, or C. However, in practice, welding, cutting or assembly activities in a manufacturing projects for an oil cargo can be under a new category so-called D. The project manager can speed up or slow down these activities by allocating or removing more resources, and these activities can be interrupted or can be resumed at any time. From the perspective of activity categories, we intend to review the literature on RCPSPs and RCMPSPs and to obtain the new research directions for solving the problems.

Project stakeholder management deals with managing and fulfilling stakeholder expec-tations and has tended to focus on the stakeholders of the organization or the project viewpoint. The thematic, spatial and temporal objects of the research were to analyze the stakeholders and projects portfolio determination based on key stakeholders of a public university in Iran in 2019. In first step, stakeholders are identified. There are 12 stakeholder groups involved the university under study. In the second step using the power/interest matrix, stakeholder categorization and positioning was performed. In the following, a mathematical model for optimizing the portfolio of projects was presented and solved. This model was developed to maximize college profit while simultaneously considering the expectations and the requirements of four key stakeholders - the board of trustees, faculty members, researchers and the Ministry of Science. These findings may mainly reflect the strategic decisions at the university.

Over the past four decades, portfolio selection has been one of the most important con-cerns of researchers, project managers, project-oriented companies, and public agencies around the world. Although numerous studies have been done in this field, still there is a room for more improvement in both theory and practice. One of the yet unspoiled topics in this field is improving and balancing the efficiency of sub-portfolios while paying attention to portfolio optimization. This study employs data-mining tools to categorize projects into sub-portfolios and rank them. Multiple Criteria Decision Making (MCDM) methods are also used to weigh the criteria on which the ranking process is based. Finally, a novel multi-objective model is designed to optimize the efficiency of sub-portfolios and the gain of the main portfolio. The model is solved by NSGA II algorithm. This study introduces a hybrid framework by which project portfolio selection process can be carried out regarding strategic alignment, cost, and risk.

The volume of rural road construction projects has increased over the last decade in Bangladesh though these projects are experiencing failure in terms of time for completion. Therefore, this study focuses on nine risk factors specifically in case of Bangladesh. The objectives are to examine and quantify the contribution of supply chain risk factors on completion time of rural road projects and to assess the prioritization of iden-tified risks. An insignificant number of researches have been performed on the effect of supply chain risks on completion time of rural roads in Bangladesh. To the best of authors’ knowledge, the three factors such as, upper contract price, prolong rainy season and time of monitoring have not yet been used as independent variables in any re-search. A linear model has been drawn and the proposed model shows that upper contract price, delay of the site handover, delay of site materials mobilization, change of scope and prolong rainy season cause time overrun, whereas, time of monitoring, delay in payment and delay in submission of contract schedule did not have significant effect on time. These findings will help the government of Bangladesh take the necessary actions to complete the projects on time.

The Health Care system is changing from the hospitalization to the home care, and the World Health Organization has announced that the rate of care-dependent elderly people in Europe will considerably increase within the next decades. Thus, scientific planning for this area is an essential factor to improve the community health. This paper aims to develop a mathematical modeling for Home Health Care Routing and Scheduling Problem and to solve it by means of Simulated Annealing (SA) algorithm considering real condition (staff vehicle traveling, conditions of patients and so forth). We permit interdependent services for patients in which they can order as many services as they want with any relation between them (Multiple Services) and supposed time window for each service. The mathematical formulation of the problem is coded in GMAS software, which is a well-known commercial software for solving optimization problems. In addition, for large-scale problems where GAMS is unable to solve, SA algorithm is applied to tackle the problems. Finally, sensitivity analysis on the most important parameters (number of services and number of patients with interdependent Multiple services) are conducted. The results reveal that when each patient can order infinite services with any relation between them, complexity of the problem increases, but SA algorithm can solve large instances with reasonable solution in the less computational time. Thus, SA algorithm shows a rational performance for large instances. Moreover, the most important factors that affect the objective value and the run time of the problems are number of patients, and number of patients with interdependent multiple services.

The resource-constrained project scheduling problem (RCPSP) is a well-known and widely studied topic. The underlying problem assumes that non-preemptions and that constant resources are restrictions imposed on project activities, which are to be scheduled, subject to precedence relation and limited resource constraints. Project activities, in RCPSP, are classified under category A. The problem is expanded to include various other activity assumptions categories, such as B and C. In the Preemptive-RCPSP, project activities are classified under category B, which refers to the activity that can be implemented using constant resources and constant durations. In the Flexible-RCPSP, project activities are classified under category C, which refers to the activities that can be executed using flexible resources over flexible durations, and preemptions are not allowed. However, in One-of-a-Kind Production companies (OKP), such as the housing industry, plastic injection moldings, and RV manufacturing, all known as “manufactured-to-order” operations, the activities are classified under category D in addition to A, B, and C, simultaneously. Category D refers to the activities that can be executed using flexible durations and flexible resources, and preemptions are allowed. In this paper, therefore, we present a new effective model in order to deal with the projects that consist of all the previous activity assumptions simultaneously to generate feasible project schedules. Case studies are included, and the results show that the resources usage is increased and the project makespan is reduced.

Servant Leadership is well known as an employee-oriented leadership style which is used by several major corporations. This work investigates the effects that Servant Leadership may have on the success of Information Technology (IT) projects. To estimate these effects via structural equation modelling (SEM) this study is based on already established models: the model of Servant Leadership developed by Van Dierendonck and Nuijten and the model of IT project success developed by Harwardt. Three of the Servant Leadership dimensions have positive impact on the success dimensions IT project. The Servant Leadership Dimension Accountability has a positive impact on the dimensions Project management success, Perception success and Result success. Authenticity has a positive impact on Project management success and Result success, whereas Forgiveness affects only Result success.

The Project Portfolio Selection is a complex process that involves many factors and considerations since the project is proposed until the project portfolio is finally selected. Project Portfolio Management is the iterative process of assessment, selection and implementation of projects, and the most important part of that is to select projects for portfolio where the or-ganization is required to identify and prioritize projects with the most objective alignment to its objectives. Since the selection of a suitable projects is very important, it is necessary to develop mathematical models to lead the organization towards the final goal. To achieve this goal, these models should reflect the organization's position, goals and priorities as much as possible. In this paper, we propose a multi - objective model for selecting the project portfolio that maximizes efficiency, quality while minimizes the risk involved in project execution.

In the past, due to the use of two-dimensional design, the probability of error in large projects increased. Over time, the need for a digital 3D model has increased in the lifetime of refineries, petrochemicals and power plants. Today, the editable digital 3D model is the basic needs of industrial plants. The Abadan Oil Refinery Co., due to its need for inspections and possible changes in the refinery, has also needed an editable 3D Digital Plant during the past few years. In this paper, with the development of a new methodology, the non-editable Navisworks® model of phase 1 and 3 of Abadan Oil Refinery was transformed into an editable Digital 3D model in AVEVA PDMS. In this methodology, the PDMS programming language called Programming Macro Language (PML) as well as .net code was used. Finally, using the Navisworks® model, these two phases, which consisted of 38 Areas, 2185 equipment, 17966 pipes, 7046 instruments, and 2617 structures were converted into an editable PDMS model for nine months.

This paper is aimed at reviewing present state of the art (1998-March 2019) on the impact of Enterprise Resource Planning (ERP) implementation in Small and Medium Enterprises (SMEs). It includes critical success factors and critical failure factors. The technique depends on writing survey for optional information gathering. It characterizes the expressions that are utilized to get explore papers from databases and advanced studies on the ERP implementation in SMEs. It additionally incorporates the consideration and prohibition criteria to im-prove nature of papers. At that point methodical audit is made on the accessible papers to research the effect of ERP usage in SMEs. Critical factors are identified for success and failure of ERP implementations and actual impact of the same on SMEs (add actual success and failure factors here besides impact). The research found in this paper has limitations in terms of the period of which research papers have been reviewed. An implicit limitation is that it does not consider an empirical study except focusing on the state of the art found in the re-search area. However, its insights will have potential benefits and the directions for future work. This paper contributes to the research on the impact of ERP implementation on SMEs either positively or negatively. It discovers critical success factors, critical failure factors and impact through secondary data collection method. The insights will help SMEs and stake-holders of SMEs and ERP service providers learn about the reasons for failure or success and take necessary course of action.