“…In the last decade, many authors like Benson (1984Benson ( , 1983, Benson and Sayin (1994), Bolintineanu (1993), Bolintineanu and El maghri (1997), Gal (1977), Isermann (1977), Tamara and Miura (1977), were interested in the linear multi-objective optimization problem:…”
Section: Introductionmentioning
confidence: 99%
“…We will approach the problem (P) via an exact penalty method inspired from Bolintineanu and El maghri (1997), El maghri (1996). Finally, we will study the all linear case (the function F is linear) and we will propose an algorithm.…”
“…In the last decade, many authors like Benson (1984Benson ( , 1983, Benson and Sayin (1994), Bolintineanu (1993), Bolintineanu and El maghri (1997), Gal (1977), Isermann (1977), Tamara and Miura (1977), were interested in the linear multi-objective optimization problem:…”
Section: Introductionmentioning
confidence: 99%
“…We will approach the problem (P) via an exact penalty method inspired from Bolintineanu and El maghri (1997), El maghri (1996). Finally, we will study the all linear case (the function F is linear) and we will propose an algorithm.…”
“…• Optimizing a scalar function over the Pareto set (introduced in [47] and investigated in [3,4,6,7,8,9,1,11,12,13,14,15,25,26,27,34,37,38] and [51] for a survey);…”
The paper deals with semivectorial bilevel optimization problems. The upper level is a scalar optimization problem to be solved by the leader, and the lower level is a multiobjective optimization problem to be solved by several followers acting in a cooperative way inside the greatest coalition, so choosing among Pareto solutions. In the so-called “optimistic problem”, the followers choose among their best responses (i.e. Pareto solutions) one which is the most favorable for the leader. The opposite is the “pessimistic problem”, when there is no cooperation between the leader and the followers, and the followers choice among their best responses may be the worst for the leader. The paper presents a general method which allows, under certain mild hypotheses, to transform a semivectorial bilevel problem into an ordinary bilevel optimization. Some applications are given.
“…• optimizing a scalar valued function over the efficient set associated to a multiobjective optimization (mathematical programming) problem; (introduced in [45] and investigated in [8,9,10,11,12,13,25,26,27,33,36,37] and [50] for a survey)…”
We present optimality conditions for bilevel optimal control problems where the upper level is a scalar optimal control problem to be solved by a leader and the lower level is a multiobjective convex optimal control problem to be solved by several followers acting in a cooperative way inside the greatest coalition and choosing amongst efficient optimal controls. We deal with the so-called optimistic case, when the followers are assumed to choose the best choice for the leader amongst their best responses, as well with the so-called pessimistic case, when the best response chosen by the followers can be the worst choice for the leader. This paper continues the research initiated in Bonnel (SIAM J. Control Optim. 50(6), 3224–3241, 2012) where existence results for these problems have been obtained
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