Search Results

Due to their ability to handle discontinuous images while having a well-understood behavior, regularizations with total variation (TV) and total generalized variation (TGV) are some of the best-known methods in image denoising. However, like other ...

In this paper, we propose two bilevel models to cope with problems concerning waste management. The first formulation stems from a multi-objective version of the problem present in the literature, while the second one improves upon the first by ...

Simultaneously enhancing the visual effects and resolution of underwater images poses a challenging task as it involves two types of image enhancement tasks, underwater image enhancement and image super-resolution. In spite of the emergence of ...

The multi-leader–multi-follower game (MLMFG) involves two or more leaders and followers and serves as a generalization of the Stackelberg game and the single-leader–multi-follower game. Although MLMFG covers wide range of real-world applications, ...

This manuscript introduces an innovative bilevel optimization approach designed to improve the deblurring process by incorporating a nonlocal p-Laplacien model with variable weights. The study includes a theoretical analysis to examine the model’...

Bilevel optimization problems embed the optimality of a subproblem as a constraint of another optimization problem. We introduce the concept of near-optimality robustness for bilevel optimization, protecting the upper-level solution feasibility ...

This paper is concerned with an optimization problem which is governed by the Kantorovich problem of optimal transport. More precisely, we consider a bilevel optimization problem with the underlying problem being the Kantorovich problem. This task ...$$

This paper addresses one class of bilevel optimization problems (BOPs) with an equilibrium at the lower level (in optimistic statement). Namely, we study BOPs with a convex quadratic optimization problem under linear constraints at the upper level ...

This paper introduces an innovative bilevel optimization approach to elevate the deblurring process. By integrating a weights variable nonlocal model with a spatially varying attached term, the methodology aims to achieve enhanced restoration ...

We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates the design and operational phases, which are represented by a mixed-integer program and discounted-cost ...

Chance constraints are a valuable tool for the design of safe decisions in uncertain environments; they are used to model satisfaction of a constraint with a target probability. However, because of possible non-convexity and non-smoothness, ...

Robot Gripper Design Optimization Problem is a well-known multi-objective optimization problem explored by various approaches in previous studies over the last few decades. The continuous parameter z plays an important role in determining a robot ...

• Presenting a new bi-level mathematical model for government-farmer interaction.
• Attention to food security and environmental damages of pesticides and fertilizers.
• Using different sensitivity analysis for a case study of rice in ...

As an important crop, rural farmers mainly plant rice on small agricultural lands. The rice supply chain provides specific features in Agricultural Supply Chain due to high demand, product diversity, and wide production area. Therefore, it is one ...

• Manufacturing as services through crowdsourcing.
• New formulation of task derivation and decomposition for operations planning of crowdsourcing.
• Coordination of product family planning and manufacturer load balancing in crowdsourced ...

Crowdsourcing in manufacturing enables collaborative product fulfillment through supply contracting, aligned with task derivation and decomposition. Effective coordination of product family planning (PFP) with manufacturing processes is crucial ...

This study presents a new imaging paradigm for overcoming the challenges limiting the improvement of the imaging quality in the electrical capacitance technique. The new imaging model enables the integration of measurement physics, sparsity-...

• A data and measurement mechanism integrated imaging method is proposed for ECT.
• A physics-informed multi-fidelity method is built for inferring image priors.
• Measurement physics and data-driven modeling paradigms are unified.
• ...

In this work, we introduce new direct-search schemes for the solution of bilevel optimization (BO) problems. Our methods rely on a fixed accuracy blackbox oracle for the lower-level problem, and deal both with smooth and potentially nonsmooth true ...

This work consists of a procedure to optimally select, among a group of candidate sites where gas stations were already located, a sufficient number of charging points in order to guarantee that an electric vehicle can make its journey without a ...

• Two models for the transformation of gas stations into electric stations.
• Each model with distinct priorities: coverage optimization and node attractiveness.
• Computational experiments consider instances with a larger number of gas ...

Bilevel problems with several followers, often called Single-Leader-Multi-Follower problems, have been proved to be very useful for modeling hierarchical interactions between agents in economics, industry, etc. When uncertainty must be taken into ...

Reducing the number of lower-level function evaluations (LFEs) is crucial to designing a bilevel evolutionary algorithm (BLEA) for bilevel optimization. Direct neighbor solution transfer (DST) is regularly used in BLEA because it can improve the ...

• We propose a bilevel improved multi-operator differential evolution algorithm.
• We propose a knowledge transfer approach to avoid misleading search.
• We propose an adaptive coordinate systems approach to improve search efficiency.

• A new mathematical model is introduced for electrical capacitance tomography.
• A ...

Low-quality tomograms constrain the potential of the electrical capacitance tomography technology. In order to break through this bottleneck and innovate reconstruction algorithms, the deep transfer learning prior (DTLP) is introduced ...