• Reformulation of the original bi-objective Mixed-Integer Linear Programming model as a bi-level optimization problem. Development an adapted solution tool, which is matheuristic involving Multi-Objective Evolutionary Algorithm particularly efficient for problems (SMS-EMOA) and Programming. Numerical evaluation proposed with application to design HSC in Midi-Pyrénées region (southern France), ...

We consider the optimal design of composite laminates by allowing a variable stacking sequence and in-plane shape of each ply. In order to optimize both variables we rely on a decomposition technique which aggregates the constraints into one unique constraint margin function. Thanks to this approach, an exactly equivalent bi-level optimization problem is established. This problem is made up of ...

The uncertainty of both the generation side and user brings certain impacts on source-load coordinated operation integrated energy system (IES). At first, characteristics IES with large-scale distributed is analyzed. Secondly, considering lower operating cost higher renewable consumption rate, a bilevel optimization model coordination based structure established, which considers side, such as w...

Purpose – The purpose of this paper is to develop a heuristic method for topology optimization of a continuum with bi-modulus material which is frequently occurred in practical engineering. Design/methodology/approach – The essentials of this model are as follows: First, the original bi-modulus is replaced with two isotropic materials to simplify structural analysis. Second, the stress filed is...

This study proposes a bi-level optimization model for the transit frequency setting problem in bi-modal networks. The objective of upper-level is to obtain solution set bus line frequencies that provide minimum total travel cost car and users. Differential Evolution (DE) algorithm employed determine optimal headways given route structure. lower-level congested multi-modal user equilibrium assig...

For the continuous manufacturing processes, the integrated optimization for production planning, scheduling, and dynamic optimization usually leads to profit improvement and better overall performance. The challenge is that the integrated optimization is often a large scale problem which is difficult to solve. To deal with the computational difficulty of the integrated problem, we first propose...