this paper addresses the continuous berth allocation problem for different types of vessels arriving during a fixed period at bulk terminals with irregular layouts, such as “L” and “F” shaped coastlines. Consideri...
ISBN:
(数字)9781837242931
this paper addresses the continuous berth allocation problem for different types of vessels arriving during a fixed period at bulk terminals with irregular layouts, such as “L” and “F” shaped coastlines. Considering the priority of large vessels in utilizing deep-water berths and berth utilization saturation, a dynamic optimization-based strategy for cargo reduction and vessel shifting is proposed. A mixed-integerprogramming model is formulated withthe objective of minimizing the total time vessels spend in port, and a multi-layer encoded particle swarm optimization algorithm is designed for solving the problem. Berth allocation and cargo reduction shifting plans for different types of vessels are provided. through numerical experiments, the proposed scheme is compared with two other schemes—one involving fixed cargo reduction shifting and the other without shifting. the results indicate that the proposed strategy has significant advantages in improving berth utilization and reducing total vessel port time.
this paper addresses the culvert maintenance planning and scheduling problem faced by the Tennessee Department of Transportation (TDOT), withthe aim of optimizing the overall condition of culverts throughout Tennesse...
详细信息
this paper considers deploying multiple UAV- mounted reconfigurable intelligent surfaces (RISs) to reflect signals from the base station (BS) to users to provide line- of-sight (LoS) communications. We aim to jointly ...
详细信息
the proceedings contain 44 papers. the special focus in this conference is on Evolutionary Multi-Criterion optimization. the topics include: A Systematic Way of Structuring Real-World Multiobjective optimization ...
ISBN:
(纸本)9783031272493
the proceedings contain 44 papers. the special focus in this conference is on Evolutionary Multi-Criterion optimization. the topics include: A Systematic Way of Structuring Real-World Multiobjective optimization Problems;IK-EMOViz: An Interactive Knowledge-Based Evolutionary Multi-objective optimization Framework;an Interactive Decision Tree-Based Evolutionary Multi-objective Algorithm;data-Driven Evolutionary Multi-objective optimization Based on Multiple-Gradient Descent for Disconnected Pareto Fronts;Eliminating Non-dominated Sorting from NSGA-III;scalability of Multi-objective Evolutionary Algorithms for Solving Real-World Complex optimization Problems;Multi-objective Learning Using HV Maximization;sparse Adversarial Attack via Bi-objective optimization;preface;visual Exploration of the Effect of Constraint Handling in Multiobjective optimization;investigating Innovized Progress Operators with Different Machine Learning Methods;end-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location;online Learning Hyper-Heuristics in Multi-Objective Evolutionary Algorithms;surrogate-assisted Multi-objective optimization via Genetic programming Based Symbolic Regression;learning to Predict Pareto-Optimal Solutions from Pseudo-weights;a Relation Surrogate Model for Expensive Multiobjective Continuous and combinatorialoptimization;pareto Front Upconvert by Iterative Estimation Modeling and Solution Sampling;an Improved Fuzzy Classifier-Based Evolutionary Algorithm for Expensive Multiobjective optimization Problems with Complicated Pareto Sets;approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables;feature-Based Benchmarking of Distance-Based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective;a Two-Stage Algorithm for integer Multiobjective Simulation optimization;partially Degenerate Multi-objective Test Problems;peak-A-Boo! Generating Multi-objective Multiple Peaks Benchmark Problems with
Pollution and global warming are current issues of concern, and their mitigation is a challenging problem. Transportation and the livestock industry are large generators of Greenhouse Gases (GHG), and therefore enviro...
详细信息
ISBN:
(纸本)9781665496070
Pollution and global warming are current issues of concern, and their mitigation is a challenging problem. Transportation and the livestock industry are large generators of Greenhouse Gases (GHG), and therefore environmental criteria must be considered in the decision-making. this paper, part of an ongoing research on the design of milk and dairy supply chains with environmental considerations, proposes a mixed integerprogramming model for the milk collection problem with heterogeneous fleet with CO2 minimization criterion. Validation of the model was made using the Gurobi solver over 15 randomly generated instances, optimally solved, and compared to a distance minimization model. the results show the prevalent use of the largest and most polluting vehicles, in particular, to cover routes with a greater number of farms far from the factory. Also, results suggest that the distance of routes can increase by up to 70% if emissions are optimized, and emissions can increase by up to 20% if distances are minimized. Finally, future research work is proposed.
It is common knowledge that using directional antennas is often mandatory for Multi-hop ad-hoc wireless networks to provide satisfying quality of service, especially when dealing with an important number of communicat...
详细信息
ISBN:
(数字)9783031599330
ISBN:
(纸本)9783031599323;9783031599330
It is common knowledge that using directional antennas is often mandatory for Multi-hop ad-hoc wireless networks to provide satisfying quality of service, especially when dealing with an important number of communication nodes [1]. As opposed to their omnidirectional counterpart, directional antennas allow for much more manageable interference patterns: a receiving antenna is not necessarily interfered by nearby emitting antennas as long as this receiving antenna is not directed towards these undesired emission beams. Two nodes then need to steer one of their antennas in the direction of the other node in order to create a network communication link. these two users will then be able to, in turn, emit and receive to and from each other. the scope of this work resides in finding a centralized algorithm to governate these antenna steering decisions for all users to instantaneously provide a valid set of communication links at any time given the positions of each user. the problem that raises is then a geometrical one that implies finding topologies of network links that present satisfying throughput and overall QoS and guarantee instantaneous connectedness i.e. the computed set of links allows any user to reach any other user in a certain number of hops. Building such optimized link topologies makes further tasks, such as routing and scheduling of the network, much simpler and faster. this problem is highly combinatorial and, while it is solvable with traditional Mixed integerprogramming (MIP), it is quite challenging to carry it out in real time. For this purpose, we propose a Deep Neural Network that is trained to imitate valid, solved instances of the problem. We use the Attention mechanism [2,3] to let nodes exchange information in order to capture interesting patterns and properties that then enable the neural network to generate valid network link topologies, even dealing with unseen sets of users positions.
We consider the rooted prize-collecting walks (PCW) problem, wherein we seek a collection C of rooted walks having minimum prize-collecting cost, which is the (total cost of walks in C) + (total node-reward of the nod...
详细信息
ISBN:
(数字)9783031069017
ISBN:
(纸本)9783031069017;9783031069000
We consider the rooted prize-collecting walks (PCW) problem, wherein we seek a collection C of rooted walks having minimum prize-collecting cost, which is the (total cost of walks in C) + (total node-reward of the nodes not visited by any walk in C). this problem arises naturally as the Lagrangian relaxation of both orienteering (find a length-bounded walk of maximum reward), and the l-stroll problem (find a minimum-length walk covering at least l nodes). Our main contribution is to devise a simple, combinatorial algorithm for the PCW problem that returns a rooted tree whose prize-collecting cost is at most the optimum value of the prize-collecting walks problem. this result applies also to directed graphs, and holds for arbitrary nonnegative edge costs. We present two applications of our result. We utilize our algorithm to develop combinatorial approximation algorithms for two fundamental vehicle-routing problems (VRPs): (1) orienteering;and (2) k-minimum-latency problem (k-MLP), wherein we seek to cover all nodes using k paths starting at a prescribed root node, so as to minimize the sum of the node visiting times. Our combinatorial algorithm allows us to sidestep the part where we solve a preflow-based LP in the LP-rounding algorithms of [13] for orienteering, and in the state-of-the-art 7.183-approximation algorithm for k-MLP in [17]. Consequently, we obtain combinatorial implementations of these algorithms (withthe same approximation factors). Compared to algorithms that achieve the current-best approximation factors for orienteering and k-MLP, our algorithms have substantially improved running time, and achieve approximation guarantees that match (k-MLP), or are slightly worse (orienteering) than the current-best approximation factors for these problems. We report various computational results for our resulting orienteering algorithms showing that they perform quite well in practice.
We propose a machine learning approach for quickly solving Mixed integer Programs (MIPs) by learning to prioritize sets of branching variables at the root node which result in faster solution times, which we call pseu...
详细信息
ISBN:
(数字)9783031080111
ISBN:
(纸本)9783031080111;9783031080104
We propose a machine learning approach for quickly solving Mixed integer Programs (MIPs) by learning to prioritize sets of branching variables at the root node which result in faster solution times, which we call pseudo-backdoors. Learning-based approaches have seen success in combinatorialoptimization by flexibly leveraging common structures in a given distribution of problems. Our approach takes inspiration from the concept of strong backdoors, which are small sets of variables such that only branching on these variables yields an optimal integral solution and a proof of optimality. Our notion of pseudo-backdoors corresponds to a small set of variables such that prioritizing branching on them when possible leads to faster solve time. A key advantage of pseudo-backdoors over strong backdoors is that they retain the solver's optimality guarantees and are amenable to data-driven identification. Our proposed method learns to estimate the relative solver speed of a candidate pseudo-backdoor and determine whether or not to use it. this pipeline can be used to identify high-quality pseudo-backdoors on unseen MIP instances for a given MIP distribution. We evaluate our method on five problem distributions and find that our approach can efficiently identify high-quality pseudo-backdoors. In addition, we compare our learned approach against Gurobi, a state-of-the-art MIP solver, demonstrating that our method can be used to improve solver performance.
the proceedings contain 18 papers. the topics discussed include: a framework for routing and spectrum assignment in optical networks, driven by combinatorial properties;coworking scheduling with network flows;a decomp...
ISBN:
(纸本)9783893180905
the proceedings contain 18 papers. the topics discussed include: a framework for routing and spectrum assignment in optical networks, driven by combinatorial properties;coworking scheduling with network flows;a decomposition branch-and-cut algorithm for the maximum cross-graph K-club problem;a robust variant of the ring star problem;towards stronger Lagrangean bounds for stable spanning trees;a branch-and-cut algorithm for the availability-aware VNF placement problem in virtualized networks;towards the solution of robust gas network optimization problems using the constrained active signature method;mixed integer linear programming for CO2 emissions minimization in a waste transfer facility location problem;and on the complexity of robust transshipment under consistent flow constraints.
Planning and resource management are important aspects of a company's operational sustainability. With good management, companies can achieve their targets while minimizing operational costs. the same goes for hos...
详细信息
暂无评论