Energy systems planning commonly involves the study of supply and demand of power, forecasting the trends of parameters established on economics and technical criteria of models. Numerous measures are needed for the fulfillment of energy system assessment and the investment plans. The higher energy prices which call for diversification of energy systems and managing the resolution of conflicts are the results of high energy demand for growing economies. Due to some challenging problems of fossil fuels, energy production and distribution from alternative sources are getting more attention. This study aimed to reveal the most proper energy systems in Saudi Arabia for investment. Hence, integrated fuzzy AHP (Analytic Hierarchy Process), fuzzy VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) and TOPSIS (Technique for Order Preferences by Similarity to Idle Solution) methodologies were employed to determine the most eligible energy systems for investment. Eight alternative energy systems were assessed against nine criteria—power generation capacity, efficiency, storability, safety, air pollution, being depletable, net present value, enhanced local economic development, and government support. Data were collected using the Delphi method, a team of three decision-makers (DMs) was established in a heterogeneous manner with the addition of nine domain experts to carry out the analysis. The fuzzy AHP approach was used for clarifying the weight of criteria and fuzzy VIKOR and TOPSIS were utilized for ordering the alternative energy systems according to their investment priority. On the other hand, sensitivity analysis was carried out to determine the priority of investment for energy systems and comparison of them using the weight of group utility and fuzzy DEA (Data Envelopment Analysis) approaches. The results and findings suggested that solar photovoltaic (PV) is the paramount renewable energy system for investment, according to both fuzzy VIKOR and fuzzy TOPSIS approaches. In this context our findings were compared with other works comprehensively.

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One of the key activities of any client is contractor selection. Without a suitable and precise method for selecting the best contractor, the completion of a project will likely be affected. In this study, we examine the use of the analytical hierarchy process (AHP) as a decision-support model for contractor selection. This model can assist project management teams in identifying contractors who are most likely to deliver satisfactory outcomes in a selection process that is not based simply on the lowest bid. In this study, an AHP-based model is tested using a hypothetical scenario in which candidate contractors are evaluated. Six criteria for the primary objective are evaluated. The criteria used for contractor selection in the model are identified, and the significance of each criterion is determined using a questionnaire. Comparisons are made by ranking the aggregate score of each candidate based on each criterion, and the candidate with the highest score is deemed the best. This study contributes to the construction sector in two ways: first, it extends the understanding of selection criteria to include degrees of importance, and second, it implements a multi-criteria AHP approach, which is a new method for analyzing and selecting the best contractor.