The time-cost optimization is amongst the most critical fields, which has an extensive range of implementation in project scheduling. Achieving a satisfactory balance between these factors can lead to an efficient construction project by reducing both the length of the project and costs at the same time. An effective balance can be achieved using various methods, depending on the situation. This study aims to incorporate the various algorithms used in the last 15 years to reach a satisfying balance between time and cost, including meta-heuristics, heuristics, and exact algorithms. A comprehensive view of the problems associated with time-cost optimization will be provided throughout this review to assist new and challenging researchers who are interested in this type of research. For this purpose, we have reviewed some objective functions and uncertainty techniques that could be employed in time-cost balancing problems. The literature review tables contain a variety of columns, including uncertainties such as fuzzy, probabilistic, interval, robust, and objective functions, along with cost and time, for the investigation of various types of balance issues. In the conclusion of this article, we will show the results of our literature review table using different types of graphic diagrams. For each main column of the table, we will show various types of diagrams to make the results easier to understand.

The paper aims to pinpoint and assess the perceived advantages and disadvantages of the Public-Private Partnership (PPP) for road development in India. Main PPP project contributors in Indian PPP road projects were polled via questionnaire. A literature review was used to select fifteen favourable characteristics and thirteen unfavourable factors for the questionnaire. Descriptive statistical analysis is used to analyze the data that was collected. The elimination of government financial restraints, project cost and time management, the reduction of government funds committed to capital investment, improved maintainability and accelerated project development are the key positive characteristics that draw PPP in Indian road projects. Excessive participation restrictions, protracted negotiating delays, ambiguity surrounding government objectives and evaluation standards, a lack of employment possibilities, and a lack of experience and the necessary skills make PPP undesirable. Both the public and private sectors can benefit from PPP in various ways. All sectors must make decisions based on proper assessment criteria during the project development stage. The decision-makers of PPP projects benefit early on from thoroughly understanding both positive and negative elements.

The industry has expressed significant concern regarding the issue of parallel machines and the influence of learning and deterioration. This research investigates non-identical parallel machine scheduling, taking into account the simultaneous consideration of learning effects, deterioration, and past-sequence-dependent setup times. Due to the existence of uncertain parameters in real-world scenarios, the processing times and due dates are assumed to be triangular fuzzy numbers. A fuzzy nonlinear mathematical model with two objective functions is presented and solved using the fuzzy Chance Constraint Programming approach. The two objectives are the summation of earliness and tardiness, as well as makespan. To achieve an efficient near-optimal Pareto front for the problem, a hybrid NSGA-II and VNS multi-objective meta-heuristic is proposed and the results are discussed. Finally, the augmented ε-constraint method is utilized to address issues with small dimensions. The computational analysis demonstrates the effectiveness of this proposed algorithm in tackling problems, especially those with substantial dimensions.

This bibliographical review gives us a clear and summarized analysis of the management tools for a water infrastructure construction project and, a tool that allows the management of water resources through the application of everything analyzed and compiled in scientific articles obtained from the Scopus database and after that it was analyzed using the VOSviewer tool, which has the complexity of analyzing a large amount of data. This analysis was carried out from the appearance of the first related investigations until the year 2023, analysis graphs were obtained from representative levels of the words “artificial intelligence”, “project management” of “construction” and “water” resource with greater interest in the analysis. The results obtained allowed us to understand the great variety of technological tools that are available today to be able to manage the construction of a project through artificial intelligence and its components that work together, likewise the application of these tools is carried out by countries as well as the United States. The United States and China are the ones that represent the greatest interest in these investigations, however this contribution is minimal to be able to generate effective solutions since each project presents its particular characteristics that technology has to adapt to. The future of these projects was also analyzed, such as the management of water resources through intelligent technologies that allow the preservation, care and maintenance of water resources, in addition to this, it is emphasized that worldwide there are already problems of droughts, lack of water resources and shortages of water in some countries. This research has the purpose of an overview for decision-making in the execution of the project at the water level and after the management of the water resource, it is important to apply these tools for their different advantages and carry it out to large-scale works in Peru subsidized by the Peruvian state since they are the most responsible for ensuring the care, maintenance and preservation of water resources.

In this paper, the authors proffer a novel mathematical model for the simultaneous optimization of facility location and network design in the presence of uncertainty, with the aim of minimizing operational and transportation costs. The proposed model constitutes a departure from conventional methods in its consideration of probable events in the real world and the incorporation of uncertainty assumptions into the mathematical framework. An algorithm based on simulated annealing is then advanced for the solution of the problem, and the performance of the algorithm is evaluated through comparison with exact methods for problems of modest size, as well as with a basic simulated annealing algorithm for larger problems. The results of these comparisons demonstrate the superiority of the proposed meta-heuristic algorithm. Finally, the robust approach is compared with four other approaches in the presence of uncertainty, with a thorough analysis of the results obtained from each of the methods conducted in a suite of sample problems.