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On inertia and ratio type bounds for the k-independence number of a graph and their relationship

DISCRETE APPLIED MATHEMATICS 2023年第1期333卷 96-109页

作者： Abiad, Aida Dalfo, Cristina Fiol, Miquel Angel Zeijlemaker, Sjanne Eindhoven Univ Technol Dept Math & Comp Sci Eindhoven Netherlands Univ Ghent Dept Math Anal Log & Discrete Math Ghent Belgium Vrije Univ Brussel Dept Math & Data Sci Brussels Belgium Univ Lleida Dept Matemat Catalonia Spain Univ Politecn Cataluna Dept Matemat Catalonia Spain Barcelona Grad Sch Math Catalonia Spain UPC Inst Matemat BarcelonaTech IMTech Catalonia Spain

For k > 1, the k-independence number alpha k of a graph is the maximum number of vertices that are mutually at distance greater than k. The well-known inertia and ratio bounds for the (1-)independence number alpha(= alpha 1) of a graph, due to Cvetkovic and Hoffman, respectively, were generalized recently for every value of k. We show that, for graphs with enough regularity, the polynomials involved in such generalizations are closely related and give exact values for alpha k, showing a new relationship between the inertia and ratio type bounds. Additionally, we investigate the existence and properties of the extremal case of sets of vertices that are mutually at maximum distance for walkregular graphs. Finally, we obtain new sharp inertia and ratio type bounds for partially walk-regular graphs by using the predistance polynomials.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： k-power graph Independence number Adjacency spectrum Polynomials k-partially walk-regular mixed integer linear programming

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An improved tabu search algorithm for solving heterogeneous fixed fleet open vehicle routing problem with time windows

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ALEXANDRIA ENGINEERING JOURNAL 2023年 64卷 349-363页

作者： Ahmed, Zakir Hussain Yousefikhoshbakht, Majid Imam Mohammad Ibn Saud Islamic Univ IMSIU Coll Sci Dept Math & Stat Riyadh Saudi Arabia Bu Ali Sina Univ Fac Sci Dept Math Hamadan Iran

The heterogeneous fixed fleet open vehicle routing problem with time windows is a very significant type of the vehicle routing problem (VRP) that aims to find the minimum fixed and vari-able cost of transportation for a heterogeneous fleet with a fixed number in which the capacity of every vehicle and usage of the vehicles should not be ignored. Also, in this problem, each customer has a special time window for servicing and each vehicle starts its route from the warehouse and ends up in one of the customers. We propose a mixed integer linear programming model of this problem. Since this problem, as well as open VRP and VRP with fixed heterogeneous fleet are hard NP problem, an improved tabu search algorithm is proposed to solve the problem. Our proposed algorithm uses a modified sweep algorithm to generate some initial solutions. Besides, a variable tabu list and some new mechanisms for intensification and diversification mechanisms are used. Numerical results are presented to show the correctness of our model and finally, the efficiency of the proposed algorithm is compared with an exact algorithm, classic tabu search and simulated annealing. The obtained results prove the efficiency of the proposed algorithm.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY license (http://***/licenses/by/ 4.0/).

关键词： Open Vehicle Routing Prob-lem with Time Window Fixed fleet Heterogeneous Tabu Search Algorithm mixed integer linear programming

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A Route Planning and Traffic Control Model for Autonomous Intersections by Minimizing Conflict Zones

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IEEE ACCESS 2023年 11卷 113678-113693页

作者： Liu, Yang Long, Kejun Wu, Wei Changsha Univ Sci & Technol Hunan Key Lab Smart Roadway & Cooperat Vehicle Inf Changsha 410114 Hunan Peoples R China Chongqing Jiaotong Univ Coll Traff & Transportat Chongqing 400074 Peoples R China

Most existing studies on autonomous intersection management (AIM) primarily focus on modeling and resolving conflicts between vehicles within an intersection, assuming predetermined routes of the autonomous vehicles (AVs) as exogenous inputs. Additionally, these studies presume scenarios in which AVs traverse the intersection at a constant speed without stopping. However, such scenarios are difficult to realize under heavy traffic demand. To address this issue, this study first discretized the intersection into numerous grids and proposed formulations to calculate the time at which the vehicles enter and exit a given grid at different speeds and accelerations based on the outer-boundary-projection dimension-reduction method. Thereafter, a bi-level programming model was established to optimize the route choices and traffic control schemes. The upper-level model aimed to minimize the conflicts within the intersection zones, considering the lane options for vehicles entering and exiting the intersection as the decision variable to optimize the AV routes. In addition, the lower-level model strived to minimize the delay for all upcoming vehicles. The time when a vehicle enters an intersection and whether it stops are utilized as decision variables. Based on the sliding time-window technique, the proposed model was transformed into a mixed-integer linear programming (MILP) problem, which is compiled by a mathematical programming language (AMPL) and solved by CPLEX. The numerical analysis shows that the proposed models significantly reduced the conflicts between the vehicles, and consequently, improved the space utilization of the intersection, reduced vehicle delays, and saved a significant amount of energy.

关键词： Optimization Traffic control Planning Safety Delays Trajectory Throughput Autonomous systems Path planning mixed integer linear programming Navigation Autonomous intersection management (AIM) route planning all-direction lanes mixed-integer linear programming (MILP) intersection

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Power Distribution Expansion Planning in the Presence of Wholesale Multimarkets

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IEEE SYSTEMS JOURNAL 2023年第1期17卷 1684-1693页

作者： Nourollahi, Ramin Gholizadeh-Roshanagh, Reza Feizi-Aghakandi, Hamideh Zare, Kazem Mohammadi-Ivatloo, Behnam Univ Tabriz Fac Elect & Comp Engn Tabriz *** Iran Azarbaijan Power Engn Consultants Co Mona Tabriz *** Iran Meganir Co Tabriz *** Iran

By deregulating the countries' electricity industry, the market players must adapt their performance to the deregulated environment. In this article, a risk-based stochastic optimization framework is proposed to model the participation of distribution system operator (DSO) in distribution expansion planning (DEP) problems in the presence of electricity wholesale multimarkets. Based on the proposed methodology in this article, the DSOs will be able to invest in the DEP by taking the benefits and imposed risks of the existing electricity multimarkets, i.e., forward contract, day-ahead, and balancing markets, to manage the risks of long-term uncertainties. The DSOs, who are the only retail suppliers in a specific region, can cover their DEP costs by offering fair retail prices to the retail consumers. Besides, DSOs could form diverse long- and short-term portfolios from the different electricity markets to procure the forecasted real loads and loss power of the network over the planning horizon. The diverse portfolio of the suppliers and a fair retail price can satisfy the DSOs to consider the multimarkets in the DEP process. Furthermore, the risk of uncertainties is modeled using the method of conditional value at risk (CVaR). Based on the obtained results, the DSO can reduce network loss costs by procuring power from markets rather than increasing the installed branches' ampacity by considering multimarkets and market price uncertainties. Besides, the obtained profit of DSO is increased by 12.16% in the proposed electricity multimarket environment.

关键词： Planning Load modeling Investment Costs Uncertainty Substations Mathematical models Conditional value at risk distribution expansion planning (DEP) electricity multimarkets mixed integer linear programming uncertainty modeling

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Hybrid and approximate algorithms for the dial-a-ride problem with adaptive ride times considering different service strategies

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ENGINEERING OPTIMIZATION 2023年第8期55卷 1263-1277页

作者： Fahmy, Sherif A. Amer Univ Cairo AUC Dept Mech Engn Cairo Egypt

The dial-a-ride problem (DARP) is that of satisfying a number of pickup and drop-off customer requests, using a fleet of vehicles. In real life, traffic conditions can affect expected travel times, and hence the satisfaction of rigid pickup/drop-off time windows and scheduled ride times. This article considers the DARP with customer-adaptive ride times under different service conditions and strategies. The problem is formulated as a mixed integer linear programming model that minimizes service cost and customer inconvenience. A hybrid genetic-variable neighbourhood search algorithm (GAVNS) is proposed to solve the problem. Experiments are conducted to compare the performance of GAVNS with that of an approximate column generation algorithm, and to evaluate the application of different strategies on service efficiency and customer satisfaction. The results demonstrate the efficiency of GAVNS, and that limited violations of time-window and ride-time constraints can improve the service efficiency while preserving customer satisfaction levels.

关键词： Dial-a-ride problem adaptive ride times mixed integer linear programming hybrid genetic-variable neighbourhood search service strategies

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Concurrent scheduling of jobs and AGVs in a flexible job shop system: a parallel hybrid PSO-GA meta-heuristic

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FLEXIBLE SERVICES AND MANUFACTURING JOURNAL 2023年第3期35卷 727-753页

作者： Amirteimoori, Arash Kia, Reza London Sch Econ & Polit Sci LSE Dept Math London England Birmingham City Univ Fac Comp Engn & Built Environm Birmingham W Midlands England

This research proposes a novel mixed integer linear programming (MILP) model along with a Parallel Hybrid PSO-GA Algorithm (PPSOGA) to address the simultaneous scheduling of jobs and Automated Guided Vehicles (AGVs) in a flexible job shop system. Wherein, finite multiple AGVs, alternative process routes, and job re-entry are considered. To the best of our knowledge, no study in the literature has highlighted the efficacy of parallel computing in the simultaneous scheduling of jobs and transporters in a flexible job shop system which remarkably reduces run-time. For this purpose, the suggested meta-heuristic is designed to be compatible with parallel computing and is compared against a number of well-known meta-heuristics (i.e., Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization) on a set of 40 benchmark instances generated using a combination of different distributions (i.e., uniform, exponential, and normal distributions). Employing two Tukey tests, the run-time means and the objective value means of all the suggested meta-heuristics are examined and compared against one another, the results of which emphasizes the superiority of the PPSOGA over all the other solution approaches in terms of the objective function's value and run-time. Finally, it is discovered that even the sequential mode of the PPSOGA (i.e., the PSOGA) produces better objective values compared to other meta-heuristics.

关键词： Flexible job shop scheduling Makespan Parallel hybrid PSO-GA algorithm Statistical test mixed integer linear programming Parallel computing

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Investigation of Electric Vehicles Contributions in an Optimized Peer-to-Peer Energy Trading System

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IEEE ACCESS 2023年 11卷 12489-12503页

作者： Al-Sorour, Ameena Fazeli, Meghdad Monfared, Mohammad Fahmy, Ashraf A. A. Swansea Univ Fac Sci & Engn Dept Elect & Elect Engn Swansea SA1 8EN Wales Swansea Univ ASTUTE Swansea SA1 8EN Wales Helwan Univ Dept Elect Power & Machines Helwan 11795 Egypt

The rapid increase in integration of Electric Vehicles (EVs) and Renewable Energy Sources (RESs) at the consumption level poses many challenges for network operators. Recently, Peer-to-Peer (P2P) energy trading has been considered as an effective approach for managing RESs, EVs, and providing market solutions. This paper investigates the effect of EVs and shiftable loads on P2P energy trading with enhanced Vehicle to Home (V2H) mode, and proposes an optimized Energy Management Systems aimed to reduce the net energy exchange with the grid. mixed-integer linear programming (MILP) is used to find optimal energy scheduling for smart houses in a community. Results show that the V2H mode reduces the overall energy costs of each prosumer by up to 23% compared to operating without V2H mode (i.e., EVs act as a load only). It also reduces the overall energy costs of the community by 15% compared to the houses operating without the V2H mode. Moreover, it reduces the absolute net energy exchanged between the community and the grid by 3%, which enhances the energy independence of the community.

关键词： Batteries Costs State of charge Peer-to-peer computing Vehicle-to-grid Tariffs Electric vehicles mixed integer linear programming Electric vehicle energy management system local consumption mixed-integer linear programming peer-to-peer energy trading

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A fast MILP solver for high-level synthesis based on heuristic model reduction and enhanced branch and bound algorithm

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JOURNAL OF SUPERCOMPUTING 2023年第11期79卷 12042-12073页

作者： Mirhosseini, Mina Fazlali, Mahmood Fallah, Mohammad K. Lee, Jeong-A Shahid Beheshti Univ Fac Math Sci Dept Comp & Data Sci Tehran Iran Univ Hertfordshire Sch Phys Engn & Comp Sci Dept Comp Sci Hatfield Herts England Chosun Univ Dept Comp Engn Gwangju 61452 South Korea

Modeling high-level synthesis (HLS) as mixed integer linear programming (MILP) affords the opportunity to integrate constraints and optimization objectives of hardware design in the form of a mathematical intermediate representation. Consequently, it is possible to improve previously developed methods to solve MILP models and customize them for application in domain-specific functions. However, the problem remains NP-hard, and solving large models requires methods that investigate the state space intelligently. Despite the high potential of branch and bound (B&B) algorithms to solve MILP models quickly, computing the best answer is still an open challenge. In this paper, we first develop three model improvement techniques that reduce the size of the search space for MILP models derived from HLS. Then, we present a new B&B algorithm to tackle the computational challenge by considering the properties of the original HLS problem. In this regard, we propose two heuristic techniques that enable the B&B algorithm to prove that some branches are not promising and should be pruned. Moreover, we have developed a best-first strategy by suggesting a new priority key calculation scheme to improve tree traversal in the B&B algorithm. Besides, the sifting method has been employed as the LP relaxation method to achieve fast processing of large models. Our proposed approach was evaluated using a set of MILP models derived from the synthesis of Mediabench data flow graphs. The experimental results indicate that our approach outperforms modern MILP solvers in terms of speed and the scale of the MILP models which can solve. According to the test results on the large MILP models, we solved models with 7254 integer and binary variables in less than 13 minutes.

关键词： High-level synthesis Hybrid branch and bound mixed integer linear programming

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Potential and economic viability of green hydrogen production from seawater electrolysis using renewable energy in remote Japanese islands

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RENEWABLE ENERGY 2023年 202卷 1436-1447页

作者： He, Hongjing Huang, Yongyi Nakadomari, Akito Masrur, Hasan Krishnan, Narayanan Hemeida, Ashraf M. Mikhaylov, Alexey Senjyu, Tomonobu Univ Ryukyus Fac Engn 1 Senbaru Okinawa 9030213 Japan King Fahd Univ Petr & Minerals Interdisciplinary Res Ctr Smart Mobil & Logist Dhahran Saudi Arabia SASTRA Deemed Univ Dept Elect & Elect Engn Thanjavur 613401 India Aswan Univ Fac Energy Engn Aswan 81528 Egypt Financial Univ Govt Russian Federat Financial markets & Financial Engn Dept Moscow Russia

Remote island power systems face high equipment costs when introducing renewable energy technologies. Lowering input costs is essential for any setup, but it is especially important for these integrated systems. Electrolysis of seawater is a good option for islands with abundant seawater resources since the green hydrogen produced may be used to create power and excess green hydrogen and Sodium hypochlorite as a by-product can be sold to reduce costs. This study compares three cases. Case 1 mixes solar, wind, and batteries to satisfy load needs. Cases 2 and 3 are based on Case 1 and apply to a seawater electrolysis plant. Case 2 does not account chemical product earnings, whereas Case 3 does. Total cost of the power system and CO2 total emissions were employed as optimization metrics, using k-means to simplify annual data and MILP to model optimal operation and capacity. Case 3 cuts costs by 16.6% and CO2 by 13.2% compared to Case 1. The initiative proposes producing and selling green hydrogen and sodium hypochlorite on remote islands by electrolyzing seawater to reduce carbon emissions and costs.

关键词： Seawater electrolysis Renewable energy systems k-means mixed integer linear programming Green hydrogen Chemical product earnings

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Optimal capacitor placement in northern region of Bangladesh transmission network for voltage profile improvement

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ENERGY REPORTS 2023年 9卷 1896-1909页

作者： Masood, Nahid-Al Jawad, Atik Ahmed, Kazi Toukir Islam, Sk. Razibul Islam, M. Asiful Bangladesh Univ Engn & Technol Dept Elect & Elect Engn Dhaka 1205 Bangladesh Univ Liberal Arts Bangladesh Dept Elect & Elect Engn Dhaka 1207 Bangladesh Power Grid Co Bangladesh Ltd Dhaka 1212 Bangladesh

This paper solves the problem of optimal placement of shunt capacitors in the northern region of Bangladesh transmission network. During network augmentation event like very high inductive reactive load condition, the weakened voltage profile of the buses can be compensated by optimum allocation of the capacitor banks. In this regard, the aim of this problem is to minimise the costs associated with capacitor banks, transmission system losses and voltage profile improvement whilst satisfying various constraints. mixed integer linear programming method is introduced for the discrete optimisation problem of placing capacitors in transmission system for cost minimisation and voltage profile improvement. In this proposed formulation, sensitivity dependent voltage magnitude is taken into account for the selection of candidate buses. It is also shown that voltage profile is linearly dependent on reactive load. Therefore, load modelling is done carefully to get a more realistic image of the overall outcomes. The proposed methodology yields integer number of capacitors of particular sizes to be placed on best suited buses. In addition, the proposed approach is applied to IEEE 39 bus system and 33 bus real transmission system of northern region of Bangladesh power system Furthermore, a thorough performance comparison with an existing state-of-the-art capacitor placement method is also performed for validation. The simulation results demonstrate that the proposed methodology is capable of producing optimised solution while successfully mitigating the low voltage issue. Moreover, the proposed approach shows enhanced voltage profile of the buses at a reduced reactive support size than the existing approach.(c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Capacitor placement Transmission system planning mixed integer linear programming Sensitivity analysis Bangladesh power system

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