This paper presents a comprehensive Integer programming (IP) model designed to optimize the robotic kitting process in industrial automotive settings. Robotic kitting, involving the efficient assembly and preparation ...
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ISBN:
(纸本)9783031586750;9783031586767
This paper presents a comprehensive Integer programming (IP) model designed to optimize the robotic kitting process in industrial automotive settings. Robotic kitting, involving the efficient assembly and preparation of kits using automated systems, plays a crucial role in modern manufacturing facilities. The proposed IP model considers various key aspects related to the cycle time, including preparation time for kit boxes on Automated Guided Vehicles (AGVs), picking time with Autonomous Mobile Robots (AMRs), image acquisition and processing time, AMR and AGV travel times, and removal time of empty component bins by AMRs. The objective is to minimize the energy consumption of AGVs in the kitting process, enhancing operational efficiency while ensuring accurate kit assembly. The formulation of the mathematical programming model allows for the consideration of flow-related activities, improving the adaptability and flexibility of the kitting process to varying order patterns. Numerical experiments demonstrate the effectiveness of the model in achieving key insights into AGVs' energy demand, contributing to advancements in mapping this process in industrial automation and logistics.
In this paper, we present methodologies for optimal selection for renewable energy sites under a different set of constraints and objectives. We consider two different models for the site-selection problem - coarse-gr...
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ISBN:
(纸本)9780998133171
In this paper, we present methodologies for optimal selection for renewable energy sites under a different set of constraints and objectives. We consider two different models for the site-selection problem - coarse-grained and fine-grained, and analyze them to find solutions. We consider multiple different ways to measure the benefits of setting up a site. We provide approximation algorithms with a guaranteed performance bound for two different benefit metrics with the coarse-grained model. For the fine-grained model, we provide a technique utilizing Integer Linear Program to find the optimal solution. We present the results of our extensive experimentation with synthetic data generated from sparsely available real data from solar farms in Arizona.
In the face of increasing billion-dollar weather events in the United States, grid resilience has become a central issue for electric utilities, operators and customers. Hence, this work presents service restoration a...
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ISBN:
(纸本)9798350381849;9798350381832
In the face of increasing billion-dollar weather events in the United States, grid resilience has become a central issue for electric utilities, operators and customers. Hence, this work presents service restoration and data-enhanced visualization for improved decision-making and resilience in the distribution system. First, we present an exploratory visual interface that increases situational awareness in the distribution system by allowing system operators to glean actionable intelligence from historical outage data. In addition, this study proposes a prescriptive service restoration framework that allows distribution system operators to manage outages in a proactive manner by leveraging outage forecasts to minimize out-of-service loads in the event of predicted outages in the distribution network. The proposed framework is formulated as a mixed integer linear programming problem and is validated using a modified IEEE 13-node test feeder. Results show a decrease in the impact of predicted outages as a result of implementing the topology optimization and service restoration framework.
Production of a digital photograph that reproduces the original scene as accurately as possible requires solution of the problem of color correction, i.e., the challenge of finding find a mapping converting the coordi...
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The advancement of renewable energy(RE)represents a pivotal strategy in mitigating climate change and advancing energy transition efforts.A current of research pertains to strategies for fostering RE *** the frequentl...
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The advancement of renewable energy(RE)represents a pivotal strategy in mitigating climate change and advancing energy transition efforts.A current of research pertains to strategies for fostering RE *** the frequently proposed approaches,employing optimization models to facilitate decision-making stands out *** from an extensive dataset comprising 32806 literature entries encompassing the optimization of renewable energy systems(RES)from 1990 to 2023 within the Web of Science database,this study reviews the decision-making optimization problems,models,and solution methods thereof throughout the renewable energy development and utilization chain(REDUC)*** review also endeavors to structure and assess the contextual landscape of RES optimization modeling *** evidenced by the literature review,optimization modeling effectively resolves decisionmaking predicaments spanning RE investment,construction,operation and maintenance,and ***nantly,a hybrid model that combines prediction,optimization,simulation,and assessment methodologies emerges as the favored approach for optimizing RES-related deci*** primary framework prevalent in extant research solutions entails the dissection and linearization of established models,in combination with hybrid analytical strategies and artificial intelligence *** advancements within modeling encompass domains such as uncertainty,multienergy carrier considerations,and the refinement of spatiotemporal *** the realm of algorithmic solutions for RES optimization models,a pronounced focus is anticipated on the convergence of analytical techniques with artificial intelligence-driven ***,this study serves to facilitate a comprehensive understanding of research trajectories and existing gaps,expediting the identification of pertinent optimization models conducive to enhancing the efficiency of REDUC development endeavors.
This paper presents a strategy based on binary labelling of nodes for the creation of anti-loop formulations from existing strategies. This strategy prevents by default the formation of odd cycles, therefore it can ha...
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This paper presents a strategy based on binary labelling of nodes for the creation of anti-loop formulations from existing strategies. This strategy prevents by default the formation of odd cycles, therefore it can have important role in iterative procedures based on generating subtour elimination constraints. It can also be used to modify the classic strategies used in problems associated to graphs. In this paper we focus on this last application. The behavior of this strategy is analyzed with two problems associated with graphs, the Asymmetric Traveling Salesman Problem (ATSP) and the Steiner Problem, where two configurations that modify the Miller-Tucking-Zemlig proposal to avoid cycles are compared. The experimental analysis shows that this strategy keep a good convergence, highlighting its use for the Steiner problem.
Research and Development (R&D) entails the generation of innovative knowledge and its practical application to address challenges. In Turkey, the advancement of R&D initiatives is fostered through the establis...
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ISBN:
(纸本)9783031671944;9783031671951
Research and Development (R&D) entails the generation of innovative knowledge and its practical application to address challenges. In Turkey, the advancement of R&D initiatives is fostered through the establishment of technoparks and R&D centers. Within these R&D centers, a wide array of project proposals is solicited, tailored to the specific domains of the companies involved. Project selection is carried out by assessing project proposals based on several criteria. This study aims to evaluate project proposals submitted to an R&D center and develop a decision-making framework to identify projects worthy of pursuit. A new set of criteria is proposed for this purpose. In the methodology, the Fuzzy Analytic Hierarchy Process (FAHP) is employed to determine the importance of the criteria, while the cumulative degrees approach is used to consolidate information from diverse sources. Additionally, a mathematical model is devised to facilitate the final project selection, taking into account constraints such as budget limitations and human resource availability.
Advancements in mathematical programming have made it possible to efficiently tackle large-scale real-world problems that were deemed intractable just a few decades ago. However, provably optimal solutions may not be ...
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ISBN:
(纸本)1577358872
Advancements in mathematical programming have made it possible to efficiently tackle large-scale real-world problems that were deemed intractable just a few decades ago. However, provably optimal solutions may not be accepted due to the perception of optimization software as a black box. Although well understood by scientists, this lacks easy accessibility for practitioners. Hence, we advocate for introducing the explainability of a solution as another evaluation criterion, next to its objective value, which enables us to find tradeoff solutions between these two criteria. Explainability is attained by comparing against (not necessarily optimal) solutions that were implemented in similar situations in the past. Thus, solutions are preferred that exhibit similar features. Although we prove that already in simple cases the explainable model is NP-hard, we characterize relevant polynomially solvable cases such as the explainable shortest path problem. Our numerical experiments on both artificial as well as real-world road networks show the resulting Pareto front. It turns out that the cost of enforcing explainability can be very small.
Reversible computing is a promising field that explores the possibility of performing computations in such a way that the initial state of the computation can be uniquely reconstructed from its final state. In this wo...
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Hydrogen and light hydrocarbon components are essential resources of the *** optimization of the refinery hydrogen system and recovery of the light hydrocarbon components contained in the gas streams are key strategie...
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Hydrogen and light hydrocarbon components are essential resources of the *** optimization of the refinery hydrogen system and recovery of the light hydrocarbon components contained in the gas streams are key strategies to reduce the operating costs for sustainable *** research efforts have been focused on the optimization of single impurity hydrogen network,and the flowrates of the hydrogen sources and sinks are assumed to be ***,their flowrates vary along with the quality of crude oil and refinery processing plans.A general superstructure of multicomponent refinery hydrogen network is proposed,which considers four components,namely H_(2),H_(2)S,CH_(4) and C_(2+),as well as the flowrate variations of hydrogen source and hydrogen *** mathematical model based on the superstructure is developed with objective functions,including the minimization of total annualized cost and the maximization of overall satisfaction of the hydrogen ***,the model considers the removal of hydrogen sulfide and the recovery of light hydrocarbon components(i.e.,C_(2+))in the *** verify the applicability of the proposed mathematical model,a simplified industrial case study with four scenarios is *** optimization results show that the economic benefit can be maximized by considering both the direct reuse of gas streams from high-pressure separator(HP gas stream)and from low-pressure separator(LP gas stream)and the recovery of the light hydrocarbon *** fuzzy optimization method can be used to guide the optimal design of the refinery hydrogen system with multi-period variable flowrates.
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