In this paper, we first present the concept of (m,n,q)-spherical hesitant fuzzy set by combining (m,n,q)-spherical fuzzy set and hesitant fuzzy set. In here, (m,n,q)-spherical hesitant fuzzy set has several advantages according to novel clusters because of including three different pa-rameters. This model produces effective solutions to deal with vagueness and complex data. The framework of (m,n,q)-spherical hesitant fuzzy set is a generalization of hesitant fuzzy set, intuitionistic hesitant fuzzy set, picture hesitant fuzzy set and t- spherical hesitant fuzzy set having a gorgeous potential of overcoming with uncertain and vagueness events. The concepts defined above have different problems within themselves. Let’s consider the t- spherical hesi-tant fuzzy set for different values of t, which is the most inclusive structure compared to other sets. Since the value t is the same for all degrees, in some cases the decision maker may have to change the value assigned by his opinion. However, for (m,n,q)- spherical hesitant fuzzy set, this situation can be solved with the least margin of error by changing any of the m, n, q values. The (m,n,q)-spherical hesitant fuzzy set is defined as the degrees of truth, indeterminacy, and falsity and sum of mth, nth and qth powers of maximum values in degrees with condition less than or equal 1 such as m, n and q are natural numbers. This concept provides a lot of advantages as three different parameters, carrying more information because of hesitant fuzzy set, hosting to several clusters in its own structure, being soft concept. In addition to, we develop the the basic operational laws like addition, power, product, scalar multiplication. Moreover, we introduce new operotors by utilizing t norm and t conorm of Aczel Alsina by adding a new parameter. The added parameter further increases the flexibility, thus increasing the comparability of the obtained results. The presented operators as following; (m,n,q)- Spherical hesitant fuzzy Aczel Alsina weighted averaging operator, (m,n,q)- Spherical hesitant fuzzy Aczel Alsina ordered weighted averaging operator, (m,n,q)- Spherical hesitant fuzzy Aczel Alsina hybrid weighted averaging operator and (m,n,q)- Spherical hesitant fuzzy Aczel Alsina weighted geometric operator, (m,n,q)- Spherical hesitant fuzzy Aczel Alsina ordered weighted geometric operator, (m,n,q)- Spherical hesitant fuzzy Aczel Alsina hybrid weighted geometric operator. On the basis of these presented operators, a algorithm is introduced to aid multi-criteria decision making problems. A example is introduced to depict the practicality and validity of our defined procedures and comparative analysis is given with helping to t-spherical hesitant fuzzy set and, there is an agreement among results.