1. Introduction
Mathematical programming problems with equilibrium constraints (MPEC) form a distinct subclass of constrained optimization models, distinguished by the presence of complementarity-type conditions or variational inequality constraints. An early contribution to the study of such optimization frameworks is the work of Harker and Pang [
1], who established foundational existence results for efficient solutions to mathematical programs with equilibrium constraints (MPEC). Given their broad applicability across various domains of science, engineering, and technological systems (see, e.g., [
2,
3,
4]), mathematical programs with equilibrium constraints (MPEC) have attracted substantial research interest in recent years. For a comprehensive discussion and recent developments on MPEC and their applications, the reader is referred to [
5,
6] and the references therein.
In recent decades, optimization problems formulated on manifolds has attracted substantial attention within the mathematical programming community, motivated by its strong theoretical foundations and extensive applicability (see, for example, [
7,
8] and the references therein). The setting of Euclidean geometry has been traditionally employed in data analysis in an extensive manner. In such a setting, the data points have been conveniently represented in terms of coordinates on the Euclidean space by several researchers (see, for instance, [
9] and the references cited therein). In recent times, however, researchers have recognized the necessity of employing non-Euclidean geometry, specifically Riemannian geometry, to accurately represent data in more complex models (see, for instance, [
9,
10,
11] and the references cited therein). Recasting classical optimization methods within a manifold framework not only broadens their scope but also introduces a number of fundamental advantages absent in the Euclidean setting. A wide class of constrained mathematical optimization problems on the Euclidean space admits reformulations into unconstrained models in the manifold framework, which often leads to a substantial reduction in the overall problem complexity; see [
6,
12] and the references therein. In addition, within the Riemannian geometric framework, several non-convex programming problems can be transformed into convex ones, see [
13,
14]. Motivated by these benefits, numerous fundamental notions of mathematical programming have been systematically generalized from Euclidean spaces to Riemannian and Hadamard manifolds in the existing literature; see, for example, [
15,
16,
17,
18,
19] and the references cited therein.
It is noteworthy that nonsmooth phenomena frequently arise in real-world optimization problems across a wide range of applications (see, [
20,
21]). Classical nonsmooth optimization has been thoroughly investigated in the frameworks of both finite and infinite dimensional Banach spaces, where the underlying linear structure plays a fundamental role (see, [
22,
23]). In recent years, however, it has become increasingly evident that nonsmooth functions arise intrinsically on smooth manifolds across a broad range of contemporary research areas (see, [
24,
25]). To address nonsmooth optimization problems beyond the Euclidean framework, the concept of Clarke subdifferentials has been generalized to Riemannian manifolds, with particular emphasis on Hadamard manifolds (see, [
26,
27]). On Hadamard manifolds, the non-positive sectional curvature of the ambient space and the existence of unique geodesics ensure that Clarke subdifferentials are convex-valued, upper semicontinuous, making it a suitable tool for nonsmooth analysis on Hadamard manifolds (see, [
8,
26,
27]). In view of this, in the present paper, the notion of Clarke subdifferentials have been employed to study NMMPEC on Hadamard manifolds.
The existing literature on mathematical programming problem with equilibrium constraints (MPEC) contain a wide range of regularity and optimality results. Foundational investigations into regularity conditions for MPEC were explored by Chen and Florian [
28]. The Abadie constraint qualification for MPEC was subsequently examined by Flegel and Kanzow [
29]. Optimality criteria for MPEC were further developed by Ye [
30]. The generalized Guignard constraint qualification, together with associated optimality criteria, was analyzed by [
31]. In the nonsmooth setting, optimality conditions for (MPEC) via convexificators were established by Ardali et al. [
32]. Moreover, various duality models for (MPEC) with vector-valued objective function were derived by Singh and Mishra [
5]. The notions of pseudonormality, local error bounds, and the Abadie constraint qualification for multiobjective
were studied in Hejazi [
33]. Pareto efficiency criteria and some constraint qualifications for smooth multiobjective (MPEC) were discussed by Zhang et al. [
34].
Various optimality criteria for single-objective and multiobjective optimization problems (MOPs) involving differentiable functions, formulated on manifolds, have been investigated in a number of works (see, for reference, [
18,
35] and the references therein). In particular, classical constraint qualifications, including the linear independence, Mangasarian–Fromovitz, Abadie, and Guignard constraint qualifications have been studied for single-objective optimization problems on Riemannian manifolds by Bergmann and Herzog [
35], while the Abadie constraint qualification has been explored for MOP in the Hadamard manifold setting by Tung and Tam [
36]. Unlike Banach spaces, manifolds generally lack an inherent linear structure, which necessitates the development of alternative analytical tools when dealing with nonsmooth functions. This challenge has motivated growing interest in nonsmooth analysis on manifolds, as reflected in recent contributions such as [
15,
16,
25,
37]. Despite this progress, several important constraint qualifications, namely the Abadie, generalized Abadie, generalized Guignard, Mangasarian–Fromovitz, Cottle, and Slater conditions, along with corresponding optimality criteria for NMMPEC, have not yet been examined on Hadamard manifolds employing Clarke subdifferential calculus. The present work addresses this gap by formulating these constraint qualifications and deriving associated optimality conditions for NMMPEC on Hadamard manifolds using Clarke subdifferentials.
Motivated by the results established in [
5,
6,
28,
30], nonsmooth multiobjective programming problem with equilibrium constraints (NMMPEC) is explored in the present article, in the setting of Hadamard manifolds. We first formulate the generalized Guignard constraint qualification (GGCQ) for NMMPEC within the setting of Hadamard manifolds. Building on this, we derive necessary Pareto efficiency conditions for NMMPEC. We then introduce several constraint qualifications specifically adapted to the NMMPEC problem, namely, the Abadie, Cottle-type, Slater-type, and Mangasarian–Fromovitz-type conditions, in Hadamard manifold framework. Various relationships among these qualifications are established, and it is further shown that each serves as a sufficient condition for GGCQ. To illustrate the applicability and importance of the theoretical results, we include non-trivial examples on several Hadamard manifold models.
The distinguishing features and key contributions of this article may be outlined as follows. Firstly, motivated by the results derived by Maeda [
22], within the framework of Hadamard manifolds, we develop a collection of constraint qualification concepts specifically adapted to
. It is noteworthy that constraint qualifications for NMMPEC have not been studied before in manifold setting using Clarke subdifferential. Secondly, the results obtained in this work extend the constraint qualifications introduced by Flegel and Kanzow [
29,
31] to the broader setting of Hadamard manifolds and to the more general class of problems, that is, NMMPEC. Furthermore, the optimality conditions derived in the present article generalize the corresponding results of Treanţă et al. [
6] to the wider framework of nonsmooth multiobjective programs with equilibrium constraints.
The remainder of this article is structured as follows.
Section 2 reviews the essential definitions and preliminary results needed for the analysis that follows. In
Section 3, GGCQ for NMMPEC is presented on Hadamard manifolds, and KKT-type necessary conditions for NMMPEC are derived. In
Section 4, we present several NMMPEC-adapt constraint qualifications and establish some interesting interrelations between them. In addition, it is demonstrated that the proposed constraint qualifications are sufficient to guarantee the validity of NMMPEC-GGCQ. Finally, in
Section 5, we summarize the main contributions of the paper and outline several directions for future investigation.
2. Preliminaries
In this paper,
will signify the Euclidean
n-space, while
stands for the set of natural numbers. The nonnegative orthant of
, written as
, is defined by
We use
to refer to the usual inner product on
. Let
. Then
Let denote an arbitrary Riemannian manifold of dimension n. The manifold is called a Hadamard manifold if it is geodesically complete, simply connected, and has nonpositive sectional curvature everywhere. Hereafter, will signify a Hadamard manifold of dimension n.
Let
. The tangent space at
is signified by
. Notably, the exponential function
is globally diffeomorphic. On the other hand,
satisfies
. Suppose that
. Then a unique minimal normalized geodesic
is guaranteed to exist for which
It is important to note that
is diffeomorphic to
. Let
be a differentiable function. Then the gradient of
,
, is the vector field on
, satisfying
for every vector field
X on
.
The definition stated below will be employed throughout the subsequent analysis; see [
16].
Definition 1. Let and . The function is called locally Lipschitz (l.l.) at with rank (, ), provided for all belonging to some open neighborhood of q, such thatwhere is the Riemannian distance between , . is called l.l. on , provided it is l.l. at each point .
Remark 1. It is worth emphasizing that certain functions which fail to satisfy the Lipschitz property in the Euclidean framework may possess this property when analyzed on Hadamard manifolds. To illustrate this phenomenon, consider the set defined by Let be a real-valued mapping given byfor every . One observes that the function fails to be Lipschitz on with respect to the standard Euclidean structure. Nevertheless, the set becomes a Hadamard manifold, say once it is endowed with the Riemannian metric provided below:where It can then be shown that the function possesses the Lipschitz property of rank 1 on (see, [20]). The definition given below can be found in [
27].
Definition 2. The set is a geodesic convex, when for every , there is a geodesic connecting y and . That is, The definitions presented below are adapted from [
37].
Definition 3. The generalized directional derivative of a l.l. function at along is given bywhere is the differential of exponential map at . Definition 4. The Clarke subdifferential of a l.l. function at is given by The following result, adapted from [
16], serves an important role in subsequent discussions.
Lemma 1. Let and be a l.l. function with rank . Then
- (a)
is compact, convex, and nonempty. Moreover, for every , and is upper semicontinuous at q.
- (b)
For every , the Clarke directional derivative satisfies - (c)
Let and be sequences such that for all and . If is a cluster point of , then .
The lemma given below is from Grohs and Hosseini [
25].
Lemma 2. Let be a l.l. function. Let be the set consisting of every element where exhibits differentiability on . Then
- (i)
is dense in ;
- (ii)
The subsequent definition is from Barani [
37].
Definition 5. Let be a l.l. function on a geodesic convex set . Then, is geodesic convex at , if for every and for every , one has is called geodesic strictly convex at
, when the inequality in (
1) holds strictly, with
. The function
is geodesic (strictly) concave at
, when
is geodesic (strictly) convex at
. A function is geodesic affine at
if it is both geodesically convex and geodesically concave at
.
Remark 2. It is worth noting that many nonconvex functions in Euclidean spaces can become geodesically convex when viewed within an appropriate manifold framework. This allows a broader class of optimization problems to be analyzed by reformulating them on manifolds. For illustration, consider the set defined as follows: We consider , as By elementary calculations, one can verify that is non-convex in . However, the set may be regarded as the image of a geodesic segment on the paraboloid of revolutionwhen this surface is endowed with the Riemannian metric defined by
Evidently, the set is geodesic convex (see, for example, [38]). Moreover, although is not convex in the Euclidean setting, it becomes geodesically convex when restricted to the set . The following theorem is from [
37].
Theorem 1. For any and a l.l. function , some and exist, satisfying:where and . The subsequent lemma from [
39] provides an extension of Motzkin’s theorem of the alternative in the context of Hadamard manifolds.
Lemma 3. Fix a point . Let , , and be matrices whose rows belong to the tangent space at p. More precisely, for , for , and for . Under these conditions, exactly one of the following statements holds, and they cannot occur simultaneously.
- (a)
The system of inequalitieshas a solution ; - (b)
The following equationhas a solution , , , such that , .
For an in-depth treatment of Riemannian manifolds and their role in optimization, the reader is referred to [
23,
27,
40,
41,
42].
3. Optimality Criteria for NMMPEC
Throughout the remainder of this paper, the subsequent
will be examined:
where
(
,
, (
),
(
),
,
(
) are l.l. on
.
Let
refer the feasible set of NMMPEC. The next definitions recall the solution concept of NMMPEC (see, [
22]).
Definition 6. A point is Pareto efficient solution of NMMPEC, provided no other exists, satisfying Definition 7. A point is weak Pareto efficient solution of NMMPEC, provided no other exists, satisfying Hereafter, we will use to refer the collection of Pareto efficient solutions of NMMPEC.
Remark 3. - (a)
The index set is called the degenerate index set at .
- (b)
It should be emphasized that the index sets defined above are determined by the particular choice of . However, for the remainder of the paper, this dependence will be left implicit whenever it is clear from the context.
Let
and
. Consider
and
, defined below:
Remark 4. The following relation evidently follows from the above definitions: The subsequent definition is from [
43].
Definition 8. Let and be any point in the closure of . The Bouligand tangent cone of at , is defined as Below, we define the notion of NMMPEC-adapt linearizing cone in manifold setting using Clarke subdifferential.
Definition 9. Let be arbitrary. The NMMPEC-adapt linearizing cone to at is defined below: Remark 5. - (a)
Definition 9 extends Definition 3.1 of Maeda [22] from the Euclidean setting to that of Hadamard manifolds. In addition, Definition 9 generalizes Definition 3.1 in Maeda [22] to the class of NMMPEC. - (b)
When , Definition 9 extends the linearizing cone notion introduced by Singh and Mishra [5] for NMMPEC.
To derive KKT-type necessary optimality criteria for NMMPEC, we now define NMMPEC-adapt GGCQ on Hadamard manifolds for NMMPEC.
Definition 10. Let . The NMMPEC-adapt generalized Guignard constraint qualification (NMMPEC-GGCQ) satisfies at , when The lemma below is employed in the derivation of the principal results of this section.
Lemma 4. Let at which NMMPEC-GGCQ holds. In such case, the system of inequalities given below:has no solution . Proof. Given that at which the NMMPEC-GGCQ holds.
Arguing by contradiction, let
satisfy (
2). Owing to the l.l. property of the components of the objective function and constraint functions of NMMPEC, we have
From Definition 9, it follows immediately that
. Hence, one may suppose, without any loss of generality, that
Again, NMMPEC-GGCQ is satisfied at
. Hence
Hence, we have some
such that
as
. Corresponding to every
(
), some
exists, for which
where
and
for every
. According to Definition 8, there exist sequences
and
such that
as
, and
Let
be defined as
Thus, for every
, one arrives at the subsequent inequalities:
Applying Theorem 1, it follows that for each
there exists
such that
and a vector
, for which
where
Evidently,
,
. In light of Lemma 1, there exits some subsequence
of
such that
and
. Further, it follows that for every
,
On the other hand, we have
Since
, we have
Employing the continuity property of the inner product, we obtain
Proceeding analogously, we obtain
which contradicts (
4), and this completes the proof. □
The subsequent theorem constitutes the main result of this section and establishes necessary criteria for optimality of NMMPEC on Hadamard manifolds.
Theorem 2. Let at which NMMPEC-GGCQ holds. Then, some real numbers , , , , , exist satisfyingand Proof. In view of Lemma 4, evidently, the system of inequalities, provided below, has no solution
:
To apply Lemma 3 at
, we identify the matrices
of Lemma 3 with the Clarke subgradients appearing in the system above. The strict inequalities (11) generate the rows of the matrix
A. The non–strict inequalities (
10), (
12), (
16) and (
17) produce the rows of the matrix
B. Finally, the equality–type relations (
13), (
14), (
15) generate the rows of the matrix
C. In view of this, by applying Lemma 3, one can obtain some real numbers
,
,
,
,
,
, which satisfy the following
where
,
,
,
and
.
We proceed by setting the following:
As a result, the following relation is obtained:
On the other hand, one has
(
),
(
),
(
),
(
). This entails that
We now define the following:
As a result, the relations stated in (
8) and (
9) hold true. The proof is therefore complete. □
Remark 6. - 1.
When all components of the objective function and the constraints associated with are smooth, Theorem 2 coincides with Theorem 4 proved in [6]. - 2.
Theorem 2 extends Theorem 3.2 of [22] by moving from smooth multiobjective programming problems to framework and by replacing the Euclidean space with a broader space, which is, Hadamard manifolds.
The significance of Theorem 2 is highlighted through the illustrative example that follows.
Example 1. Consider the set defined as Then becomes a Riemannian manifold (see [40]) when equipped with the subsequent metric:and is a Hadamard manifold (see, [18]). Let and , the exponential function is defined as given below: We study the following NMMPEC on :where (, , . The feasible set of (P1) is given by (see, Figure 1): Let . Then, we have From the above expressions, it follows that Consequently, we yield that Thus, NMMPEC-GGCQ holds at . We choose , , , . Then, we obtainwhere , , , . Therefore, every condition in Theorem 2 is verified. Example 2. Let denote the Poincaré half-plane, given below: Then becomes a Riemannian manifold when endowed with the metric defined below (see, [36]):and is also a Hadamard manifold (see, [27]). For any and , is determined by (see, [27]): If , is given bywhere Further is given by Consider the following NMMPEC on :where (), , and . refers the feasible set of (), see, Figure 2. That is Now, we choose the feasible element . The following relations for the tangent and linearizing cones can be easily obtained: Consequently, we yield that Hence, we conclude that NMMPEC-GGCQ holds at .
By choosing multipliers , , , , we obtainfor suitable selections , , , . Hence, every requirement of Theorem 2 is satisfied. In this section, an NMMPEC has been considered on Hadamard manifolds. Further, we have deduced KKT-type necessary conditions for Pareto efficiency for NMMPEC by employing the GGCQ.
4. Constraint Qualifications for NMMPEC on Hadamard Manifolds
We now adapt various classical constraint qualifications and investigate their NMMPEC-specific counterparts on manifolds.
Definition 11. The NMMPEC-adapt Abadie constraint qualification (NMMPEC-ACQ) holds at if: Definition 12. The NMMPEC-adapt generalized Abadie CQ (NMMPEC-GACQ) holds at if: The lemmas stated below are straightforward consequences of the definitions of NMMPEC-ACQ and NMMPEC-GACQ.
Lemma 5. If NMMPEC-ACQ is satisfied at , then NMMPEC-GACQ is also satisfied at .
Lemma 6. If NMMPEC-GACQ holds at , then NMMPEC-GGCQ holds at .
The following definitions are extended from Maeda [
22] for NMMPEC on Hadamard manifolds.
Definition 13. The NMMPEC-adapt Cottle-type CQ (NMMPEC-CCQ) holds at , if for every the subsequent system:has a solution . Definition 14. The NMMPEC-adapt Slater-type CQ (NMMPEC-SCQ) holds at if ), and , are geodesic convex, , are geodesic concave, , , are geodesic affine. Furthermore, for every the subsequent system:has a solution . Definition 15. The NMMPEC-adapt Mangasarian-Fromovitz CQ (NMMPEC-MFCQ) holds at if , , , are linearly independent, and moreoverhas a solution . The lemmas presented below establish several nontrivial relationships among the constraint qualifications specifically developed for .
Lemma 7. If NMMPEC-CCQ holds at , then NMMPEC-GGCQ also holds at .
Proof. It is given that
. Moreover, CCQ is satisfied at
. Hence, some
exists, such that (
22) hold true. On the other hand, there exists some
such that
Let
. Then, in view of Definition 9, it follows that
We assert that
. Consider a sequence
. Define
as
Evidently,
as
. In light of (
25), (
26) and (
27), we have
For each element in
, let us consider another sequence
. Hence, we may define
as
Evidently,
as
. In view of Theorem 1, for every
, some
,
, and
exist, satisfying
where
It is obvious that as
,
. From Lemma 1, there exists some subsequence
of
, such that
and
. In light of (
28), for every
, we get
Since
, for large enough
k, we obtain
Analogously, for large enough
k, for every
, we obtain
For every
, it follows from the continuity property of
that
Proceeding analogously, we can obtain
Then it follows from (
29), (
30), (
31) and (
32) that
Without restricting generality, it is relevant to assume that
for all
k. This indicates that
Similarly, for any choice of
,
holds. Hence, we obtain
Therefore, the proof is complete. □
Lemma 8. If NMMPEC-MFCQ holds at , then NMMPEC-CCQ holds at .
Proof. It is given that NMMPEC-MFCQ holds at . This implies that , , , are linearly independent.
Again, some
exist, satisfying (
24). Hence, we have
Arguing by contradiction, let NMMPEC-CCQ fail to hold at
. Then there exists some
for which
has no solution
.
From Lemma 3, we obtain
,
,
,
, not each zero, and
,
,
for which
where
,
,
,
,
. From (
33) and (
35) it follows that
Combining (
33) and (
36), we yield that
,
,
,
,
,
. Then, it follows from (
35) that
From the linearly independence of
,
,
,
, one has
resulting in violation of our hypothesis. Therefore, the proof is complete. □
Lemma 9. If NMMPEC-SCQ holds at , then NMMPEC-CCQ holds at .
Proof. It is given that NMMPEC-SCQ holds at
. Hence
), and
are geodesic convex,
,
are geodesic concave,
,
,
are geodesic affine. Again, for each
, we have some
, such that
For each
(
),
(
)),
(
),
(
),
(
) it follows that
We now define
. Hence
, we arrive at
Thus NMMPEC-CCQ holds at , and the proof is complete. □
The main findings of this section are combined in the theorem stated below.
Theorem 3. Consider that is a Pareto efficient for NMMPEC, and suppose that . If any one of the CQ listed in Definitions 11–15 is fulfilled at , then the condition NMMPEC-GGCQ is satisfied at this point. Furthermore, there exist multipliers for , for , for , and for , such that the relations (8) and (9) are satisfied. Remark 7. Theorem 3 generalizes Theorem 4.1 of Maeda [22] from MOP to NMMPEC and extends it from Euclidean space to Hadamard manifolds. The findings obtained in this section can be outlined and conveniently visualized from
Table 1 and
Figure 3.
Example 3. Let stand for the collection of all symmetric real matrices. Suppose that refers to the trace of any square matrix . Consider , which consists of matrices that are symmetric and positive definite. Let . When equipped with the metric given below, becomes a Hadamard manifold (see, [24,44,45,46]):for any arbitrary , . Let and . Then, is defined below:where Exp refers the matrix exponential (see, [44]). The inverse of is a function from to , defined below:where Log refers the usual logarithm on (see, [44]). The Riemannian gradient of is determined bywhere refers the Euclidean gradient of F at (see, [24]). Examine the subsequent NMSIPMCwhere and are l.l. functions and . Let be the feasible set of (P). Then, Notably, is a Pareto efficient solution of (P), and one has Hence, one can verify that NMMPEC-ACQ does not hold at . Considering , , , , one has As a matter of fact, we observe that even though NMMPEC-ACQ is not satisfied at , the conclusions of Theorem 3 may still hold. Hence, this numerical example demonstrates that NMMPEC-ACQ constitutes a sufficient, but not a necessary, condition for the validity of the KKT conditions at a Pareto efficient solution of NMMPEC.
This section develops a collection of CQ specifically designed for NMMPEC on Hadamard manifolds. Various nontrivial relationships among these qualifications are analyzed. In particular, it is shown that each of these conditions guarantees the validity of NMMPEC-GGCQ for NMMPEC.
5. Future Research Directions and Conclusions
In this work, we have examined nonsmooth multiobjective mathematical programming problems with equilibrium constraints within the Hadamard manifold framework. GGCQ tailored to NMMPEC have been formulated in the Hadamard manifold setting, and necessary conditions for Pareto efficiency have been derived. Furthermore, several constraint qualifications specifically adapted to NMMPEC, including NMMPEC-ACQ, NMMPEC-GACQ, NMMPEC-CCQ, NMMPEC-SCQ, and NMMPEC-MFCQ, have been introduced and on Hadamard manifolds. The relationships among these qualifications have been systematically investigated, and it has been shown that each of them provides sufficient conditions for the validity of NMMPEC-GGCQ. Finally, illustrative examples on Hadamard manifolds have been presented to highlight the applicability and relevance of the theoretical results.
The theoretical developments presented in this paper broaden earlier results obtained by Maeda [
22] by extending them to the Hadamard manifold set-up and to the class of NMMPEC. Additionally, the constraint qualification concepts originally investigated by Flegel and Kanzow in [
29,
31] are generalized here to a non-Euclidean geometric setting and adapted to a substantially wider family of optimization problems. Furthermore, the optimality conditions derived in this work encompass and extend those established by Treanţă et al. [
6], thereby covering a more general class of nonsmooth multiobjective problems with equilibrium constraints.
5.1. Applications and Implications
Optimization on Hadamard manifolds underpins many contemporary geometric algorithms, including Riemannian gradient, subgradient, and proximal methods that exploit nonpositive curvature for stability and convergence (see, [
24,
25] and the references therein). Such methods are increasingly important in applications involving manifold-valued data and imaging, where nonsmooth optimization problems naturally arise (see, [
46,
47]). The KKT-type conditions and constraint qualifications developed for NMMPEC in the present manuscript may be extended to develop numerical algorithms to solve NMMPEC on Hadamard manifolds. We intend to pursue this problem in our future research endeavours.
5.2. Limitations and Future Work
Throughout the theoretical results presented in this manuscript, local Lipschitz continuity is imposed on all objective and constraint functions. Consequently, the results derived in this paper are not applicable to problems in which this regularity assumption is violated. This may be regarded as a limitation of the present work. Moreover, duality models for NMMPEC on Hadamard manifolds have not been investigated in this paper. Furthermore, investigating numerical algorithms to solve real-world NMMPEC on Hadamard manifolds would be an exciting direction of future study.
The findings of this study open up multiple avenues for further investigation. In particular, exploring constraint qualifications for nonsmooth MOP with switching constraints on Hadamard manifolds via convexificators is a promising direction for future research. In addition, in light of the results established by Patriksson and Wynter [
48], the results derived in this paper may be extended to stochastic optimization problems with equilibrium constraints on Hadamard manifolds. Further, another promising future research direction is the study of second-order optimality criteria and duality results for NMMPEC on Hadamard manifolds. These will be our future courses of study.