## 1 Introduction  
An intelligent system is any system or tool which can support informed decision-making [1, 2]. The task of decision making is one of the challenging tasks, which eventually results in the realization or failure of a specific scenario or case. For instance, in a business scenario, a decision support system helps managers to take the right decisions regarding certain complicated problems that arise due to the rapidly changing environment.  
Decision-making becomes more challenging in circumstances where it is grounded on multiple criteria. To deal with problems involving multiple criteria, multiple-criteriadecision-making (MCDM) or multiple-criteria decision analysis (MCDA) analyze these multiple conflicting criteria to get a more appropriate decision [3; 4]. There are a number of MCDM problems and methods classifications but the major difference among them is the way a solution is obtained that might be either implicit or explicit.  
Modern decision support systems (DSS) are equipped with the command of multi-criteria decision analysis (MCDA) methods to help decision-makers in taking appropriate decisions in complex scenarios. Because of the usefulness of multi-criteria decision-making systems, investigators are struggling to integrate them with machine learning algorithms for providing better alternatives for accurate decision-making [5; 6; 7]. DSS has widely been used in diverse fields of application, such as agriculture [8], the energy sector [9; 10], business [11], and so on. Different fields use different methods of decision-making for problems ranging from simple to complex scenarios [12; 13]. Due to the effectiveness of DSS in the decision-making process, researchers are attracted to providing more reliable and robust solutions to solve current as well as future problems. Intelligent decision support systems are an active area of study for researchers where they try to explore new algorithms and propose methods for improving the capabilities of decision support systems.  
In light of the importance and effectiveness of DSS in various domains, a systematic literature study was conducted covering the period 2015 to early 2020. The objective of the presented review is to identify the scope, trends, and methods exploited in various domains for the design and development of a decision support system using multiple criteria. Based on the objective, the following research questions are defined and researched throughout the study.  
* RQ1: What are the major application areas of IDSS for intelligent decision-making, based on multi-criteria?
* RQ2: What is the significance and impact of multicriteria-based decision support systems (DSS) for solving problems in diverse application areas?
* RQ3: What are the major problems solving approaches, algorithms, and methods used for multicriteria-based decision-making?  
The paper is structured as follows. A detailed discussion regarding the search method used for the subject study is shown in Section 2. Section 3 clarifies the procedure for evaluating the papers chosen for the review. The analysis of the papers and their results are discussed in Section 4. Section 5 presents the threats to the validity of the conducted research while Section 6 provides the conclusion.