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Conflict-free en-route operations with horizontal resolution manoeuvers using a heuristic algorithm

AERONAUTICAL JOURNAL 2020年第1275期124卷 767-785页

作者： Cecen, R. K. Cetek, C. Anadolu Univ Eskisehir Turkey Eskisehir Tech Univ Eskisehir Turkey

Aircraft conflict resolution is an important part of air traffic control operations. This study presents a mixed integer linear programming model (MILP) using a space discretisation technique to deal with aircraft conflict resolutions in en-route flight operations. The purpose of space discretisation is to concentrate on only the significant points of the airspace. The model integrates the multi entry point approach with an airspeed adjustment technique in the horizontal plane. The model aims to generate conflict-free trajectories while minimising the total changes in entry points and airspeed values. A new heuristic algorithm was developed due to the complexity of the problem. The computational results demonstrated that the proposed approach resolved aircraft conflicts for 450 different traffic scenarios in less than a minute. Considerable fuel savings were achieved with no significant increase in delay or flight time compared to conventional vectoring techniques in a fixed entry point airspace structure.

关键词： aircraft conflict resolution mixed integer linear programming heuristic algorithm air traffic flow management

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Scheduling Model for the Practical Steelmaking-continuous Casting Production and heuristic algorithm Based on the Optimization of "Furnace-caster Matching" Mode

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ISIJ INTERNATIONAL 2020年第6期60卷 1213-1224页

作者： Yang, Jian-ping Wang, Bai-lin Liu, Qian Guan, Min Li, Tie-ke Gao, Shan Guo, Wei-da Liu, Qing Univ Sci & Technol Beijing State Key Lab Adv Met Beijing 100083 Peoples R China Univ Sci & Technol Beijing Engn Res Ctr MES Technol Iron & Steel Prod Beijing 100083 Peoples R China Jiangsu Boji Spraying Syst Co Ltd Yangzhou 225267 Jiangsu Peoples R China Laiwu Iron & Steel Grp Yinshan Sect Steel Co Ltd Jinan 271104 Shandong Peoples R China

Considering the "furnace-caster matching" modes, this paper focuses on the scheduling problems from practical steelmaking-continuous casting production lacking refining span. Aiming at the improvement on quality and output of steel products, a mathematical model is established with multi-objective optimization including the minimum earliness/tardiness of starting cast times, the shortest waiting times of heats among different processes and the shortest idle times of converters. A heuristic algorithm based on the optimization of "furnace-caster matching" mode is developed to solve this model, which involves two procedures of device assignment and conflict elimination. Through the detailed analysis on workshop layout and production rhythm, four classes of matching modes of "refining furnace-caster" are proposed to perform the assignments of refining furnaces. The assignments of converters rely on three categories of greedy strategies in terms of minimizing conflictions among heats. A rough scheduling solution with some possible conflicts among heats is obtained through combining "furnace-caster matching" modes and greedy strategies. Then applying the linear programming method to eliminate the conflicts and generate the final solution. Based on the proposed algorithm and the improved genetic algorithms, simulation experiments are carried out by introducing actual production plans as instances. The results indicate that heuristic algorithm based on the optimization of "furnace-caster matching" mode is the right candidate owing to its acceptable scheduling solutions with the better process matching relations and the highlighted performances under crane constraint. Currently, the proposed model and algorithm have been successfully used in a large converter steel plant in China.

关键词： steelmaking-continuous casting workshop layout scheduling model heuristic algorithm furnace-caster matching

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A heuristic algorithm combining Pareto optimization and niche technology for multi-objective unequal area facility layout problem

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2020年第0期89卷 103453-000页

作者： Liu, Jingfa Liu, Jun Yan, Xueming Peng, Bitao Guangdong Univ Foreign Studies Sch Informat Sci & Technol Guangzhou 510006 Peoples R China Guangdong Univ Foreign Studies Guangzhou Key Lab Multilingual Intelligent Proc Guangzhou 510006 Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Peoples R China

The unequal area facility layout problem (UA-FLP) is the problem of placing departments with different areas in a facility so that departments satisfy some given objectives and constraints. In this paper, two objectives including the material handling cost and the closeness rating are optimized. Based on the quasi-physical strategy, we introduce an extrusive elastic potential energy based on the overlapping distance between departments into the layout system. After a novel handling approach of the non-overlapping constraint formed by executing the gradient method with an adaptive step length and subsequent department deformation strategy is developed to deal with the interference among departments and between any department and the facility, the problem is first converted into an optimization problem without the non-overlapping constraint. Then, we use a new heuristic algorithm that combines the local search based on the Pareto optimization and the global optimum search based on the niche technology to obtain Pareto-optimal solutions of the problem. In the proposed heuristic algorithm, in order to overcome the shortcomings of low efficient search toward the diversity of solutions in classical Pareto optimization method, we propose a heuristic layout updating strategy and a niche technology. To improve the convergence of the algorithm to the Pareto front, a mechanism of evolution of population named a feasible layout bank in the algorithm based on the local search and global optimum search is proposed. Two sets of representative instances from the literature with the size of the problem up to 62 departments are tested. The experimental results show that the proposed heuristic algorithm is an effective method for solving the multi-objective UA-FLP.

关键词： Facility layout problem heuristic algorithm Multi-objective optimization Pareto optimal Global optimization

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Green parallel machines scheduling problem: A bi-objective model and a heuristic algorithm to obtain Pareto frontier

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2020年第6期71卷 967-978页

作者： Zandi, Arash Ramezanian, Reza Monplaisir, Leslie KN Toosi Univ Technol Dept Ind Engn Tehran Iran Wayne State Univ Dept Ind & Syst Engn Detroit MI USA

Sustainability consciousness in manufacturing has become an interesting topic for many researchers in recent years. There is also more concern in many companies about reducing energy consumption in manufacturing. Improving environmental health and safety, production cost saving, access to governmental incentives such as grants and tax credits and also improving the brand image are the most important reasons which is leading many companies to an environmental-friendly production planning. For example, one of the most applicable scheduling problems deals with planning jobs on numbers of parallel machines. In such an application, different machines have different technologies and different speed and power of energy consumption in manufacturing similar jobs. This article introduced a mathematical formulation which models the green parallel machines scheduling problem with total energy consumption and total completion time as objectives. Due to high computational complexity of the proposed model, a heuristic algorithm is developed to obtain the exact Pareto frontier of these two objectives with a polynomial complexity. Numerical experiments are presented to show the efficiency and speed of the proposed algorithm compared to solving the model using the optimisation software directly.

关键词： Green scheduling sustainable manufacturing parallel machines energy consumption heuristic algorithm

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Multi-agent System with an Optimized heuristic algorithm for Energy Management Solutions

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JOURNAL OF INTERCONNECTION NETWORKS 2022年第SUPP03期22卷 2144007-2144007页

作者： de Lin, Bao Tlili, Iskander Baseer, Mohammad Abdul Yunnan Power Grid Co Ltd Kunming 650000 Yunnan Peoples R China Thermal Syst Renewable Energy Nanotechnol Tunis Tunisia Majmaah Univ Elect Engn Dept Al Majmaah Saudi Arabia

A Smart Hybrid Home (SHH) system studies power concerns for individual clients with an off-grid electricity connection are studied in a Smart Hybrid Home (SHH) system. The creation of autonomous hybrid electricity systems has been regarded as a way to improve energy independence. The primary objective is to ensure efficient management of energy. Detailed modeling is proposed in which the solar energy component is regarded as the significant source to achieve this aim. A multi-agent energy management system (MA-EMS) is presented in this article. It also includes the storing devices for power (Fuel Cell/Capacitors) for safe power delivery. The technical performance of the decentralised solution is in line with the existing central solution, which offers improved financially and operationally for the implementation and operation of the autonomous method. Furthermore, an IT-management system is created and described to guarantee that the system functions correctly utilizing a multi-agent structure. The proposed electricity management system is meant to recognize multi-agent jobs and comprehend probable situations based on energy attributes and requirements. The findings showed that the method suggested meets the aims of an operational database taken from different climatic services using the Matlab/Simulink Application set for the Smart Electricity Management Method. By implementing the proposed technique the power consumption is increased to 410 kw, and it improves the efficiency rate to 88.4%.

关键词： Multi-agent system energy management heuristic algorithm smart grid

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A heuristic algorithm for balancing workloads in coverage modeling

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COMPUTERS ENVIRONMENT AND URBAN SYSTEMS 2022年 92卷 101746-101746页

作者： Xu, Jing Murray, Alan T. Church, Richard L. Wei, Ran Univ Calif Santa Barbara Dept Geog 1832 Ellison Hall Santa Barbara CA 93106 USA Univ Calif Riverside Sch Publ Policy Riverside CA 92521 USA

Location covering problems are important tools for supporting facility siting decisions in both the natural and built environment. However, facility workloads often vary significantly using classic coverage modeling approaches, because service allocations are not explicitly considered. In addition to capacitated extensions that are traditionally relied on, an explicit way to balance workloads in coverage modeling is to track workload difference between pairs of sited facilities, with a goal of minimizing variation. Such an approach provides an effective way to consider workload equity, but a byproduct is increased complexity and computationally difficulty in solving associated models by exact methods. This paper proposes a heuristic algorithm to address the computational difficulties in balancing workloads in coverage modeling. The proposed algorithm incorporates interchange along with simulated annealing, taking advantage of problem-specific knowledge to derive high-quality solutions in an efficient manner. Empirical studies demonstrate that the proposed algorithm is able to generate nondominated solutions that effectively approximate the Pareto optimal frontier, but do so in a computationally efficient manner.

关键词： Maximal covering Workload equity Bi-objective optimization heuristic algorithm

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Hybrid heuristic algorithm Based On Improved Rules & Reinforcement Learning for 2D Strip Packing Problem

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IEEE ACCESS 2020年 8卷 226784-226796页

作者： Zhu, Kai Ji, Naihua Li, Xiang Dong Qingdao Univ Technol Sch Informat & Control Engn Qingdao 266400 Peoples R China

A hybrid heuristic algorithm based on improved rules and reinforcement learning is proposed to solve the 2D strip packing problem (2DSPP). Firstly, the scoring rules based on the skyline algorithm are improved by considering the "two-step" successive items with a set of width relaxation factors. The improved scoring rules can reduce space waste efficiently. Secondly, as a reinforcement learning approach, the Deep Q-Network (DQN) is established to get the initial rectangular items sequence and at the same time as an essential supplement for the placement rules. It can improve space utilization and prevent the algorithm from falling into the local optimum. Combining the new "two-step" placement rules and DQN, the heuristic algorithm based on simple random algorithm (SRA) is proposed and finally called reinforcement learning based simple random algorithm (RSRA). Experiments on eight datasets by five algorithms have been conducted for comparison. Results show the RSRA has achieved the best performance on eight datasets (C, N, CX, NT, 2sp, NP, ZDF, BWMV) and has dropped Ave. Gap% by 45.86%, 45.16%, 30.89% and 20.56% than GRASP, SRA, IA, ISH respectively. It can be concluded that the RSRA algorithm would achieve better performance than the other four algorithms on eight datasets, especially on the larger datasets.

关键词： heuristic algorithms Reinforcement learning Strips Optimization Approximation algorithms Space debris Simulated annealing 2D strip packing problem (2DSPP) heuristic algorithm improved rules deep Q-Network (DQN) reinforcement learning

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Proposing a novel heuristic algorithm for university course timetabling problem with the quality of courses rendered approach;a case study

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ALEXANDRIA ENGINEERING JOURNAL 2020年第5期59卷 3355-3367页

作者： Tavakoli, Mohammad Mehdi Shirouyehzad, Hadi Lotfi, Farhad Hosseinzadeh Najafi, Sayed Esmaeil Islamic Azad Univ Sci & Res Branch Dept Ind Engn Tehran Iran Islamic Azad Univ Najafabad Branch Dept Ind Engn Esfahan Iran Islamic Azad Univ Sci & Res Branch Dept Math Tehran Iran

University course timetabling problem has been and id being considered as an operational issue by researchers. The purpose of University Course Timetabling Problem is to allocate academic courses to the lecturers, time slots and classrooms which must be executed in such a manner to promote to quality of education. In this context, a three-stage heuristic algorithm consisting of lecturers, time slots and classes is proposed. By applying the Days of lecturers' attendance to total days of planning ratio, Lecturer quality level in planning context, Offering the simultaneous prerequisite and main courses to the all course ratio, Courses presented in the last time-slot to total courses ratio, Surplus classroom capacity to classroom capacity ratio, Full-time lecturer to total lecturers ratio and Number of classrooms assigned to each lecturer to total available classroom ratio indexes, the planning obtained through this newly proposed algorithm is assessed and the response quality is determined. The available data of the subject university's industrial engineering department is fed in MATLAB software through this algorithm with the objective to have the University Course Timetabling Problem as the output. At its experimental stage, the output is measured through the same indexes revealing that course presentation by the lecturers is 96% of the possible optimum. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.

关键词： University course timetabling heuristic algorithm Educational quality Educational planning

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A heuristic search algorithm for Hamiltonian circuit problems in directed graphs

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WIRELESS NETWORKS 2022年第2期28卷 979-989页

作者： Jin, Dawei Li, QingQin Lu, Min Zhongnan Univ Econ & Law Sch Informat & Safety Engn Wuhan 430073 Hubei Peoples R China

A heuristic search algorithm is given that determines and resolves the Hamiltonian circuit problem in directed graphs. The heuristic information of each vertex is a set composed of its possible path length values from the starting vertex, which is obtained by the path length extension algorithm. A detailed analysis of algorithm examples shows that the heuristic algorithm can greatly reduce the number of processing nodes compared to the backtracking algorithm without information;meanwhile, the algorithm's time complexity is related to the number of loops in the directed graph. If a directed graph G(V, E) only contains loops that contain the starting point, then the Hamiltonian problem of G can be determined in polynomial time. The algorithm is implemented using C++ and Python programming, and all of the test graphs are generated by the random graph algorithm. The experiments show that the heuristic algorithm can reduce the number of extended nodes by at least 10% in directed random graphs with no or only a few loops. This heuristic algorithm can save time in applications that perform tasks while extending nodes because it reduce the number of extended nodes.

关键词： Hamiltonian circuit Directed graph heuristic algorithm Random graph Time complexity

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A heuristic approximation algorithm of minimum dominating set based on rough set theory

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2022年第1期44卷 752-769页

作者： Guan, Lihe Wang, Hong Chongqing Jiaotong Univ Sch Math & Stat Chongqing 400074 Peoples R China

The minimum dominating set of graph has been widely used in many fields, but its solution is NP-hard. The complexity and approximation accuracy of existing algorithms need to be improved. In this paper, we introduce rough set theory to solve the dominating set of undirected graph. First, the adjacency matrix of undirected graph is used to establish an induced decision table, and the minimum dominating set of undirected graph is equivalent to the minimum attribute reduction of its induced decision table. Second, based on rough set theory, the significance of attributes (i.e., vertices) based on the approximate quality is defined in induced decision table, and a heuristic approximation algorithm of minimum dominating set is designed by using the significance of attributes (i.e., vertices) as heuristic information. This algorithm uses forward and backward search mechanism, which not only ensures to find a minimal dominating set, but also improves the approximation accuracy of minimum dominating set. In addition, a cumulative strategy is used to calculate the positive region of induced decision table, which effectively reduces the computational complexity. Finally, the experimental results on public datasets show that our algorithm has obvious advantages in running time and approximation accuracy of the minimum dominating set.

关键词： Graph theory Minimum dominating set Rough set heuristic algorithm

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