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.

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.

This exploratory paper will investigate the concept of supply chain risk management involving supplier monitoring within a cooperative supply chain. Inventory levels and stockouts are the key metrics. Key to this concept is the assumptions that (1) out-of-control supplier situations are causal triggers for downstream supply chain disruptions, (2) these triggers can potentially be predicted using statistical process monitoring tools, and (3) carrying excess inventory only when needed is preferable as opposed to carrying excess inventory on a continual basis. Simulation experimentation will be used to explore several supplier monitoring strategies based on statistical runs tests, specifically "runs up and down" and/or "runs above and below" tests. The sensitivity of these tests in detecting non-random supplier behavior will be explored and their performance will be investigated relative to stock-outs and inventory levels. Finally, the effects of production capacity and yield rate will be examined. Results indicate out-of-control supplier signals can be detected beforehand and stock-outs can be significantly reduced by dynamically adjusting inventory levels. The largest benefit occurs when both runs tests are used together and when the supplier has sufficient production capacity to respond to downstream demand (i.e., safety stock) increases. When supplier capacity is limited, the highest benefit is achieved when yield rates are high and, thus, yield loss does not increase supplier production requirements beyond its available capacity.

This paper presents an overview on recent studies on the role of gender in corporate governance. We study the recent works on the relationship between gender and firms’ financial performance as well as the relationship between gender and firms’ interest in global warming. According to our survey, it appears that firms with the presence of females had more concerns on green gas effects than other male oriented corporations did. Moreover, according to our survey, when a female member joins the board of directors, most investors consider this as a positive signal for profitability. In other words, it appears that the presence of female contributes to firm’s financial performance.

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.

Differential Search (DS) algorithm is a new meta-heuristic for solving real-valued numerical optimization. This paper introduces a new method based on DS for solving Resource Constrained Project Scheduling Problem (RCPSP). The RCPSP is aimed to schedule a set of activities at minimal duration subject to precedence constraints and the limited availability of resources. The proposed method is applied to PSPLIB case studies and its performance is evaluated in comparison with some of state of art methods. Experimental results show that the proposed method is effective. Also, it is among the best algorithms for solving RCPSP.

Construction operations are blamed as one of important causes of green gas effects. During the past few decades, there has been tremendous efforts to reduce the negative effects of construction operations on environment. This paper presents an application of data envelopment analysis to measure the relative efficiencies of the researches accomplished by various countries around the world on green construction or green management. The study expects countries that produce higher amount of CO2 accomplish more quality research articles. To do this, the study performs a survey using three keywords; namely “green construction”, “green building” and “sustainable building” on Scopus database and found 8692 articles over the period 1965-2019 where one of these keywords, at least, was used in their abstracts, keywords or titles. We also use three measures of h-index, I-10 and total publications repre-sentative of quality and quantity of the outputs produced by researchers. The study considers 28 countries responsible for at least 90% of CO2 emission for measuring the relative efficiency program using data envelopment analysis. The results indicate that Hong Kong was the only efficient country followed by Singapore with relative efficiency of 0.67.

Maintenance engineering plays an important role in management of oil and gas projects. This paper presents a dynamic programming approach for resource allocation in oil and gas projects. The study presents a dynamic programming approach to allocate human resources for repairment of oil and gas equipment. Many heavy equipment normally needs to be repaired on predetermined scheduled and the process normally takes days or even weeks. The process can be divided into three stages of disassembling the equipment, executing the repairment and assembling the equipment. The proposed model of this paper models the problem into a classical dynamic programming and using a real-world case study, the implementation of the proposed model is described.

The purpose of this paper is to examine the existing risks for the offshore project and risk weighting using the fuzzy best worst method (FBWM). In offshore oil projects, we face six major risks. Each of these risks is divided into smaller risks leaving us to have a total of 34 risks. Some of these risks are internal and some are external risks. In this method, first, the experts of this field determined the best and the worst type of risk. Then, using the experts’ opinions, the study compared the remaining risks with the two selected risks and the other weights are determined. In our survey, “Technical Risk and Project Execution” is the most important risk factor followed by “Political Risk and Sanctions”, “Market risk”, “Manage-ment risk”, “Financial risk and currency fluctuations” and “Environmental risk”.

In project management, a schedule is considered as a list a project's milestones, activities, and deliverables, normally with some start and finish time schedule, which are estimated by some information incorporated in the project schedule including resource allocation, budget, task duration, and linkages of dependencies and scheduled events. This paper presents a comprehensive review of the studies associated with project scheduling. The study uses Scopus database as a primary search engine and covers 3370 records over the period 1963-2019. The records are statistically analyzed and categorized in terms of different criteria. Based on the survey, "decision support systems" is the keyword which has carried the highest densities followed by heuristics methods. Among the most cited articles, papers published by researchers in Germany have received the highest citations (9084), followed by United States (7058) and Belgium with 4853 citations.