An improved algorithm to minimize the total completion time in a two-machine no-wait flow-shop with uncertain setup times

Since scheduling literature has a wide range of uncertainties, it is crucial to take these into account when solving performance measure problems. Otherwise, the performance may severely be affected in a negative way. In this paper, an algorithm is proposed to minimize the total completion time (TCT) of a two-machine no-wait flowshop with uncertain setup times within lower and upper bounds. The results are compared to the best existing algorithm in scheduling literature: the programming language Python is used to generate random samples with respect to various distributions, and the TCT of the proposed algorithm is compared to that of the best existing one. Results reveal that the proposed one significantly outperforms the best one given in literature for all considered distributions. Specifically, the average percentage improvement of the proposed algorithm over the best existing one is over 90%. A test of hypothesis is conducted to further confirm the results.

The utilization of project risk monitoring and control practices and their relationship with project success in construction projects

Risk monitoring and control is often poorly implemented in construction projects because of a failure to monitor and manage identified risks. Construction companies experience significant losses due to project managers' lack of project risk monitoring and control in construction projects. Most studies have concentrated on risk identification, risk assessment, and risk analysis processes while neglecting crucial risk management processes of risk control, risk monitoring, and risk response. The lack of research on these three crucial processes highlights a gap in the literature concerning how these processes can increase the delivery of successful projects. The purpose of this study was to examine whether the utilization of project risk monitoring and control practices was related to project success in construction projects in the United States. An electronic survey instrument was used to collect data from a sample of 50 construction project managers in the Dallas-Fort Worth area in the state of Texas, in the United States. Spearman rho correlation analysis was used to examine the relationship between project risk monitoring and control practices and project success. The results of this study indicated that all project risk monitoring and control practices, including risk reassessment, risk audits, contingency reserves analysis, and risk status meetings, were significantly and positively related to project success in construction projects. One of the recommendations presented in this study was that future research should conduct the same study in developing countries to see if the study’s findings remain the same and generalizable. The study concluded that construction organizations should regularly consider the importance and usage of project risk monitoring and control practices and apply them to improve the success rate of a project.

The attractiveness of public-private partnership for road projects in India

The objective of this paper was to have a study on the perceptions of stakeholders of Public-Private Partnership (PPP) projects for factors affecting the attractiveness of road projects in India. A questionnaire survey was conducted among major PPP project participants of Indian PPP road projects. Fifteen attractive factors were shortlisted through a literature survey for designing the questionnaire. Collected data was analyzed with factor analysis and descriptive statistical analysis. The findings resulted in three components: effectiveness of the private sector, effective time and cost management, and the public sector’s economic benefit. Eight factors were identified as highly affecting the attractiveness of PPP in Indian road projects. PPP provides ample diversity of net benefits to both the public and private sectors. During the project development stage, both sectors have to formulate decisions based on appropriate assessment criteria. Therefore, the reflection of attractive factors will assist the public-sector to select PPP in the road sector. It also helps to establish the strategy for road projects using PPP.

Review of conventional metaheuristic techniques for resource-constrained project scheduling problem

This paper is concerned with an overview of the Resource-Constrained Project Scheduling Problem (RCPSP) and the conventional meta-heuristic solution techniques that have attracted the attention of many researchers in the field. Therefore, researchers have developed algorithms and methods to solve the problem. This paper addresses the single-mode RCPSP where the objective is to optimize and minimize the project duration while the quantities of resources are constrained during the project execution. In this problem, resource constraints and precedence relationships between activities are known to be the most important constraints for project scheduling. In this context, the standard RCPSP is presented. Then, the classifications of the collected papers according to the year of publication and the different meta-heuristic approaches applied are presented. Five weighted articles and their meta-heuristic techniques developed for RCPSP are described in detail and their results are summarized in the corresponding tables. In addition, researchers have developed various conventional meta-heuristic algorithms such as genetic algorithms, particle swarm optimization, ant colony optimization, bee colony optimization, simulated annealing, evolutionary algorithms, and so on. It is stated that genetic algorithms are more popular among researchers than other meta-heuristics. For this reason, the various conventional meta-heuristics and their corresponding articles are also presented to give an overview of the conventional meta-heuristic optimizing techniques. Finally, the challenges of the conventional meta-heuristics are explored, which may be helpful for future studies to apply new suitable techniques to solve the Resource-Constrained Project Scheduling Problem (RCPSP).

Development of a hybrid AHP and Dempster-Shafer theory of evidence for project risk assessment problem

In this paper, a new hybrid AHP and Dempster-Shafer Theory of Evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, four groups of risk factors, including Properties, Operational and Technological, Financial, Strategic risk factors, are considered. Then using an L24 Taguchi method, several experiments with various dimensions have been designed and solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index (VI), Reduced Risk Indicator (R.R.I%), and Solving time. The findings indicated that, compared to the classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

Project scheduling and buffer management: A comprehensive review and future directions

In the project management, buffers are considered to handle uncertainties that lead to changes in project scheduling which in turn causes project delivery delay. The purpose of this survey is to discuss the state of the art on models and methods for project buffer management and time optimization of construction projects and manufacturing industries. There are not literally any surveys which review the literature of project buffer management and time optimization. This research adds to the previous literature surveys and focuses mainly on papers after 2014 but with a quick review on previous works. This research investigates the literature from project buffer sizing, project buffer consumption monitoring and project time/resource optimization perspectives.

The effect of project management through e-business and garage sales on poverty reduction

Poverty is one of the significant problems, and almost all countries worldwide face poverty issues that negatively impact society. This study is written to investigate the students' knowledge and awareness of poverty and interest level in conducting e-business and garage sales. Also, examine the relationship of knowledge and awareness on students' intention to conduct e-business and garage sales. There were 152 respondents from the same university who participated in this study. The data analyzed using descriptive and inferential statistics performed by SPSS-23 and SmartPLS 3.3.3. The survey showed that the student's knowledge and awareness of poverty are still lacking and need improvement. Half of the respondents said they are not familiar with SDG1, and they were not aware that their university has done an event related to SDG1 and poverty. There were 25% and 85% of students interested in conducting e-business and garage sales that increased their pocket money and reduced poverty rates among university students. Overall, this study's result shows a positive response from all respondents, and most of them have general ideas of poverty. In addition, this study has identified that the variable knowledge and awareness have a significant positive effect on student's intention to conduct e-business and garage sales.

Assessing public sector road construction projects’ critical success factors in a developing economy: Definitive stakeholders’ perspective

This study assessed the critical success factors (CSFs) of public-sector road construction projects execution from the perspective of definitive stakeholders associated with such projects by drawing on in-depth semi-structured interviews (16) and surveys (372) in Ghana, thirty-four (34) CSFs were identified. Using Relative Importance Index (RII), Spearman Rank Correlation Coefficients, and Kendall’s Coefficient of Concordance and the Chi-square test of significance statistics, the top ten most important factors in descending order are: the absence of political interference, project continuity by successive governments, adequate project funding, support from financial institutions and donor agencies and countries, government commitment to the project, absence of clientelism, absence of nepotism, no political corruption, payments of contractors on time and absence of court injunction or legal suit and land litigations. This study contributes to road construction CSFs in the context of public sector road construction in developing economies.

Adoption of a multi-criteria approach for the selection of operational measures in a maritime environment

In recent times, there have been developments in the maritime industry that underscore the need to optimise operations to yield maximum productivity. Apart from this, stakeholders in this industry have also advocated improvements in seaport operations' critical areas. However, there is no known study in which the relationship between performance criteria and seaport operation measures is investigated. This study proposes a framework for selecting operation measures for the maritime industry. It uses stakeholders' expectations for operational criteria and fuzzy logic to design the framework. Nine criteria were considered in the framework, while Fuzzy VIKOR (VIsekriterijumska optimizacija I KOmpromisno Resenje) and fuzzy Shannon entropy were incorporated into it. The framework's applicability was tested using information that was obtained from Tin can port, Lagos, Nigeria. During this process, hinterland traffic diversion (A1), congestion pricing (A2), off-dock container yards (A3), Fast rail shuttles (A4), expanded rail connections (A5) were considered as alternatives for seaport operational measures. When the developed framework was used to analyse the collected information from Tin Can port, Lagos, Nigeria, the fuzzy VIKOR index ranked the alternatives as A1 » A2 » A3 » A5 » A4. Therefore, this study's insights show that mathematical models can be used to make informed seaports decisions.

A new hybrid method for selecting the best project manager: TODIM-FSE and Behavioral TOPSIS

This work aims to present the application of Multi-Criteria Decision-Making methods to the process of recruiting candidates for the position of project manager, considering aspects of the decision maker's preferences in uncertain and risk scenarios. Applied, descriptive and experimental, made up of the combined employment TODIM-FSE methods for multi-criteria classification of available candidates, and the method Behavioral TOPSIS, to choose the ideal project manager. The hybrid application of the Multi-Criteria Decision-Making methods TODIM-FSE, method based on Prospect Theory, and Behavioral TOPSIS, which considers the concept of loss aversion of Economic Behavior, is essentially innovative. When using TODIM-FSE and Behavioral TOPSIS, it was verified the explicit incorporation of the risk profile of the decision maker - aggressive, neutral, or conservative - in the context of aversion or propensity to the risks associated with the management of a project. Through the personal recruiting process from a large Brazilian organization, the possibility of adopting the hybrid model resulting from the combination of the two methods in a real situation was validated. Such validation allowed us to conclude that the candidates' classifications and choices, previously normally accepted, were at odds with the profile and risk propensity of the decision makers.