1. Introduction
We all know the importance and efficiency of duality theory in the study of extremization problems. Mishra and Mukherjee [
1] used the Pareto optimum concept to analyze a duality theory for classical multiobjective variational problems. Wolfe dual and Mond–Weir dual have been considered, under the generalized
-convexity hypotheses, for establishing weak and strong duality theorems. Later, Bhatia and Mehra [
2] established sufficient optimality conditions and duality theorems for multiobjective continuous-time variational problems under
B-type I and generalized
B-type I assumptions of the involved functions. Also, by using invexity assumptions, Nahak and Nanda [
3] formulated Wolfe and Mond–Wei duals for a family of non-differentiable multiple-objective variational models. Xiuhong [
4], taking into account the innovative ideas formulated in Leitmann [
5] and Swam [
6], stated a duality for some multiobjective control problems. Pereira [
7,
8] investigated the control design associated with autonomous vehicles and provided a maximum type principle for state-constrained impulsive control problems. In 2000, a generalized invexity was proposed for the duality theory associated with multi-objective programming problems (see Aghezzaf Hachimi [
9]). Efficiency and duality outcomes for some classes of multiobjective control problems with generalized invexity have been stated by Reddy and Mukherjee [
10] and Zhian et al. [
11]. Moreover, Kim and Kim [
12] formulated generalized type I invexity to investigate duality in vector optimization. Antczak [
13,
14] studied
G-invex variational problems by providing both (necessary and sufficient) optimality criteria and the associated duality theory. In order to state a necessary and sufficient condition such that each Kuhn–Tucker point is an optimal solution, Arana-Jiménez et al. [
15,
16] studied KT-invex and FJ-invex control-type problems. Hachimi and Aghezzaf [
17] established sufficiency and duality in multiobjective optimization problems governed by generalized type I functions. Later, Khazafi et al. [
18,
19] extended the previous point of view and introduced a generalized type I univexity and
-type I functions. Zhang et al. [
20] established sufficiency criteria and duality results for multi-objective control problems with
G-invexity assumptions. Recently, Treanţă [
21] formulated well-posedness results in some optimization problems involving variational inequality constraints. Moreover, Saeed et al. [
22] stated optimality conditions for multiobjective minimization models implying semi-infinite constraints and generalized
-type I functions. Abdulaleem and Treanţă [
23] formulated and proved optimality criteria and a duality in
E-differentiable multiobjective problems with
-type I functions. Very recently, Marghescu and Treanţă [
24] studied a family of control problems generated by approximately pseudo-convex multiple integral functionals.
In this paper, we continue and extend the analysis performed in Treanţă et al. [
25], where the authors stated and proved necessary and sufficient criteria of efficiency for a feasible point in a class of controlled variational models involving multiple integral-type cost functionals. Concretely, based on a class of multi-objective variational control models involving path-independent curvilinear integrals (not multiple integrals as in Treanţă et al. [
25]), we introduce a dual problem. In addition, various duality results are formulated and proved in order to study and investigate the relationships between the set of solutions for these two variational control problems. The principal novelty elements included in the present paper are given by the original and innovative ideas and the new mathematical framework used to prove the main theorems (the presence of partial derivatives of the control variable is a new element in this research area). Also, due to the applications in physics of the functionals used in this study (namely, second-type curvilinear integrals calculate the mechanical work conducted by a variable force to move its point of application along the considered curve), the present work has various implications in control theory, robotics, economic systems, or energy optimization. Furthermore, the path independence of the considered integrals implies a symmetry of the partial derivatives associated with the functionals in question.
2. Problem Formulation
In the following, we state notation and definitions that will be used to establish the principal results associated with this paper. In this regard, for any two vectors, , we consider the following rules:
(i) if and only if for all ;
(ii) if and only if for all ;
(iii) if and only if for all ;
(iv) if and only if and .
Let be a compact set in , a piecewise smooth curve that links the points a and b in , and let be some index sets. Suppose is a differentiable mapping (piecewise) of , and is the partial derivative of related to in D. Also, consider is a differentiable mapping (piecewise) of , and is the partial derivative of related to in D. Denote by A the space of state functions with norm , and denote by Y the space of control functions with the uniform norm, as well.
In the following, motivated by the physical applications (mechanical work) of the involved functionals, we study the multi-objective variational control model involving path-independent curvilinear integrals, defined as followed:
where
, is a continuously differentiable
v-dimensional functional, and
is a
-class functional.
Next, we denote
and
as
and
, respectively, and
and
as
and
, respectively. Also, we consider the notations
Let
denote the
set of all feasible points of (Primal), that is
The following three definitions present different types of solutions for the above-mentioned class of extremization problems, considered in the rest of the paper.
Definition 1. A pair is named weakly efficient point of (Primal) if there is no other feasible pair satisfying Definition 2. A pair is named efficient point of (Primal) if there is no other feasible pair satisfying Definition 3. A pair is named properly efficient point of (Primal) if there is such that the following inequalityholds, for each , and for some k, satisfyingwhenever and . Next, we recall the classical definition of a strictly increasing function.
Definition 4. A real-valued function is named strictly increasing if and only if The definitions presented below play an essential role in the formulation and demonstration of the basic results obtained in this paper. Specifically, we introduce (for the first time) the concepts of H-type I, strictly H-type I, pseudo-quasi-H-type I, striclty-pseudo-quasi-H-type I, weak-pseudo-quasi-H-type I, strong-pseudo-quasi-H-type I, and weak-striclty-pseudo-quasi-H-type I for the pair , where are defined as above.
Let
, be the range of
where
, and
, be the range of
where
.
Definition 5. For , if there exists a smooth vector-valued functional with as a strictly increasing function, a smooth vector-valued functional with as a strictly increasing function, with , and with , such thatandhold, for all , then the pair is named H-type I at on (related to and ϑ). If (1) and (2) are fulfilled for each , then the pair is named H-type I on related to , ν and ϑ.
Definition 6. For , if there exists a smooth vector-valued functional with as a strictly increasing function, a smooth vector-valued functional with as a strictly increasing function, with , and with , such that the following inequalitiesandhold, for all , then the pair is named strictly-H-type I at on related to and ϑ. If (3) and (4) are fulfilled for each , then the pair is named strictly-H-type I on related to and ϑ.
Definition 7. For , if there exists a smooth vector-valued functional with as a strictly increasing function, a smooth vector-valued functional with as a strictly increasing function, with , and with , such thatandhold, for all , then is named pseudo-quasi-H-type I at on (related to and ϑ). If (5) and (6) are fulfilled for each , then the pair is named pseudo-quasi-H-type I on related to and ϑ.
Definition 8. For , if there exists a smooth vector-valued functional with as a strictly increasing function, a smooth vector-valued functional with as a strictly increasing function, with , and with , such thatandhold, for all , then is named strictly-pseudo-quasi-H-type I at on related to and ϑ. If (7) and (8) are fulfilled for each , then the pair is named strictly-pseudo-quasi-H-type I on related to and ϑ.
Definition 9. For , if there exists a smooth vector-valued functional with as a strictly increasing function, a smooth vector-valued functional with as a strictly increasing function, with , and with , such thatandhold, for all , then is named weak-pseudo-quasi-H-type I at on related to and ϑ. If (9) and (10) are fulfilled for each , then the pair is named weak-pseudo-quasi-H-type I on related to and ϑ.
Definition 10. For , if there exists a smooth vector-valued functional with as a strictly increasing function, a smooth vector-valued functional with as a strictly increasing function, with , and with , such thatandhold, for all , then is named strong-pseudo-quasi-H-type I at on related to and ϑ. If (11), (12) and (13) are fulfilled for each , then the pair is named strong-pseudo-quasi-H-type I on related to and ϑ.
Definition 11. For , if there exists a smooth vector-valued functional with as a strictly increasing function, a smooth vector-valued functional with as a strictly increasing function, with , and with , such thatandhold, for all , then is named weak-strictly-pseudo-quasi-H-type I at on related to and ϑ. If (14) and (15) are fulfilled for each , then the pair is named weak-strictly-pseudo-quasi-H-type I on related to and ϑ.
3. Main Results
In this section, we associate with (Primal) a dual problem, named (Dual), in order to study and investigate the relationships between the set of solutions for these two variational control problems. In short, duality provides a connection between two unconstrained or constrained extremization models, namely, the primal problem (a minimization/maximization problem), and the dual problem (a maximization/minimization model). In fact, the main goal is to ensure that the existence of a solution to one problem ensures the existence of a solution to onother problem (under various assumptions).
Thus, we introduce the following:
where
and
are defined as in the previous section.
Let
B be the
feasible solution set in (Dual),
The next result presents a weak-type duality between the variational models considered. Specifically, under various assumptions of the pair , this theorem establishes that the value of the cost functional associated with the primal model cannot be greater than the value of the cost functional associated with the dual model.
Theorem 1. Let and and assume that one of the following hypotheses is satisfied:
(a) the pair is strictly H-type I at with respect to and ϑ;
(b) the pair is strictly-pseudo-quasi-H-type I at with respect to and ϑ;
(c) the pair is strong-pseudo-quasi-H-type I at with respect to and ϑ.
Then, the following relations cannot holdand Proof. Let
and
be feasible solutions in the considered multiple-objective models (Primal) and (Dual), respectively. We proceed by contradiction and suppose, contrary to the result, that (16) and (17) are satisfied. Further, we consider that we are in hypothesis a). Since the pair
is strictly
H-type I at
with respect to
and
, the following inequalities are satisfied
and
Since every
is a strictly increasing functional, the inequalities (16) and (17) yield
and
By (18), (20) and (21), it follows that
Multiplying each inequality (22) by
, and then adding both sides of the obtained inequalities, we obtain
Multiplying each inequality
by
, and then adding both sides of the obtained inequalities, it follows
Using the feasibility of
in (Dual) together with (24), we obtain
Adding both sides of (23) and (25), it results that the inequality
is verified, contradicting the feasibility of
in (Dual). Thus, we complete the proof under hypothesis (a). In a similar way, we can prove the current theorem under each of the hypotheses given in (b) and (c). □
If we consider weaker generalized invexity hypotheses, then a weaker result is true, as follows:
Theorem 2. Let and and assume that one of the following hypotheses is satisfied:
(a) the pair is H-type I at with respect to , and ϑ;
(b) the pair is pseudo-quasi-H-type I at with respect to and ϑ;
(c) the pair is weak-strictly-pseudo-quasi-H-type I at with respect to and ϑ.
Then the following relation cannot hold The following two results present a strong-type duality between the variational models considered. Concretely, under the same hypotheses formulated in the above two theorems and considering to be an efficient (weakly efficient) point of (Primal), we state that is an (weakly efficient) efficient point of (Dual). Since the proofs for these two theorems are (in large part) the same, we provide only the proof of Theorem 4.
Theorem 3. Let be an (weakly efficient) efficient point of (Primal), that is, the following necessary efficiency conditionsare satisfied at this point. Then is a feasible solution of (Dual). In addition, if Theorem 1 holds, then is an (weakly efficient) efficient point of (Dual). Theorem 4. Let be a properly efficient point of (Primal), that is, the following necessary efficiency conditionsare satisfied at this point, and assume the hypotheses in Theorem 1 are fulfilled. Then is a feasible solution of (Dual). In addition, is a properly efficient point of (Dual) and the objective values at these points are equal. Proof. Since
is a properly efficient point of (Primal), there exist
and a piecewise smooth function
such that the above-mentioned conditions are satisfied at this point. Thus,
is feasible in the dual model (Dual). By Theorem 1, it follows that
is an efficient point of (Dual). Next, we prove that
is a properly efficient point of (Dual) by the technique of contradiction. Then, there exists
and
such that the following inequality
is valid for
and
k, verifying
We consider the index set
and denote by
the set of indices of cost functionals satisfying the inequality (27). By
we denote the set of indices of cost functionals defined as follows
. The inequality (26) is satisfied for all
. Then, we set
, where
denotes the cardinal of the set
. In consequence, (26) and (27) yield
By the definition of the set
, (26), (27) and (28), it follows that
This is a contradiction with Theorem 1. Hence,
is a properly efficient point of (Dual), and the optimal cost functional values are equal in the dual and the primal problems. □
In the following, we illustrate the main findings of the current paper with some numerical examples.
Illustrative example 1. Let
,
, where
is a square fixed with the diagonally opposite points
and
in
. Now, we consider the vector-valued functional
, defined by
, that generates the curvilinear integral functional
Also, let us define
and consider
. We have
Thus, the above-mentioned real-valued double integral functional is not convex at
. On the other hand, if we consider the strictly increasing function
defined by
, then we obtain
with
and
. Similar computations can be written for
with
,
,
. Thus, the curvilinear integral functionals given above form the pair
and it is
H-type I at
. Moreover, since all the hypotheses in Theorem 4 are satisfied, the Lagrange multipliers
, then
is a properly efficient point of the associated (Dual) and the objective values at these points are equal.
Illustrative example 2. Let
and
and
be a piecewise curve linking the diagonally opposite points
and
în
. Let us define the multidimensional first-order PDE-constrained control problem given as follows:
subject to
We aim to find the control function
(that determines the state function
) which satisfies the dynamical system (29) with respect to boundary condition (31), such as to minimize the objective vector functional. Also, we are interested in affine state functions.
Consider
is an efficient solution to (MCP2). Then, by the classical necessary efficiency conditions, there exist piecewise smooth functions
and
, satisfying
Now, we introduce the following increasing functions which help to simplify the previous problem: .
From the efficiency of
to (MCP2), there exist the piecewise smooth functions
and
, such that the
H-necessary efficiency conditions are satisfied at
as follows:
for all
, except at discontinuities. Indeed, the above system is easier to study in comparison to solving the system (32)–(35), which is an advantage of
H-necessary efficiency conditions. Now, taking into account relations (38) and (39), we consider
.
Case 1. Assume that
are constant functions, say
and
, where
. Therefore, Equation (37) gives
which shows that
is a constant function on
. Taking into account (29), it follows that
Applying the boundary condition (31), we obtain
and
. Therefore, we obtain
Now, one can clearly observe that the point as given above is a point associated with (MCP2) since there exist satisfying , and , such that conditions (36)–(39) are fulfilled.
Further, let us show that
at
, is an efficient solution of (MCP2). For all
, we have the following:
and
By solving Equation (29), we obtain
and putting these values in Equations (40) and (41), we obtain
and
Now, we have to find the state function
which satisfies the boundary conditions (34). From the equality constraints (29), we have
Applying the necessary Euler–Lagrange PDE, we obtain
Applying boundary condition (31) on the above solution, we obtain that
and
. Hence,
Therefore, the inequalities (42) and (43) together with the solution
conclude that
Also,
Case 2. If we assume that are not constant functions, we obtain a contradiction with the hypothesis (we are interested in affine state functions).
In conclusion, we have provided a detailed computation on a concrete numerical example, establishing the key steps in calculating the efficient solution.