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A hybrid heuristic algorithm FOR THE FUZZY OPEN VEHICLE ROUTING PROBLEM WITH RISK PREFERENCE

JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2025年第3期21卷 1812-1831页

作者： Cao, Erbao Wang, Xin Yang, Yanbin Ge, Hongyu Hunan Univ Coll Econ & Trade Changsha 410079 Peoples R China Hunan Prov Key Lab Logist Informat & Simulat Tech Changsha 410079 Peoples R China Dalian Univ Technol Sch Energy & Power Engn Dalian 116024 Peoples R China

Risk preference is an important factor influencing allocation decisions in reality. However, by taking effective measures, decision-makers can successfully make optimal decisions based on risk preferences. In this paper, we investigate the impact of decision-maker risk preference and open vehicle routing in the case of fuzzy demand. A novel fuzzy programming with recourse (FPR) model formulation is proposed for the open vehicle routing problem with trapezoidal fuzzy demand (OVRPFD). The goal is to minimize the delivery cost while taking into account the decision-maker's preferences. To generate high-quality solutions, this work proposes a hybrid heuristic algorithm that incorporates several key components, including Monte Carlo simulation, genetic algorithm, and adaptive large neighborhood search. The efficiency of the algorithm is compared in experiments, revealing the superior performance of the algorithm. The impact of the decision-maker's risk preference on various costs is also investigated separately. The proposed models and algorithms provide high-quality solutions for decision-makers with risk preferences, thus facilitating decision-making that takes risk preferences into account.

关键词： Open vehicle routing problem hybrid heuristic algorithm fuzzy sets risk preference

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A hybrid heuristic algorithm for high-speed rail line planning problem with multiple transport organization modes

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RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT 2025年 60卷

作者： Li, Shiqi Chen, Xinghan Lang, Maoxiang China North Artificial Intelligence & Innovat Res Collect Intelligence & Collaborat Lab Beijing 100072 Peoples R China Beijing Jiaotong Univ Sch Traff & Transportat Key Lab Transport Ind Big Data Applicat Technol Co Beijing 100044 Peoples R China Katholieke Univ Leuven Fac Econ & Business Res Ctr Operat Res & Stat ORSTAT B-3000 Leuven Belgium

This study investigated the line planning problem for high-speed rail (HSR) trains that must satisfy both passenger and freight transportation demand and operate in coordination on a common line. It is necessary to maximize the utilization of the transport capacity of the HSR network by applying multiple transport organization modes to simultaneously allocate passenger and freight demands and solve the operational schemes of passenger and freight trains in parallel. A multi-objective mixed integer linear programming (MO-MILP) model was constructed with individual HSR passenger and freight carriages as decision objects. To solve the NP-hard problem, a hybrid heuristic algorithm combining column generation and genetic algorithms was designed. The algorithm introduces strategies such as carriage candidate set, train formation and stops, and demand updating. The numerical experiment was based on real operation data of China's Dalian-Harbin HSR line and was compared with the existing solution method. The results indicate that the optimization effect of the line planning problem is remarkable.

关键词： High-speed rail Transport organization mode Line planning hybrid heuristic algorithm Carriage candidate set

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hybrid heuristic algorithm for two-dimensional steel coil cutting problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2012年第3期62卷 829-838页

作者： Zheng, Weimin Ren, Peiyu Ge, Peng Qiu, Yanqing Liu, Zhusheng Sichuan Univ Dept Ind Engn Sch Business Chengdu 610065 Peoples R China

This paper is concerned with the problem of two-dimensional cutting of small rectangular items, each of which has its own deadline and size, from a large rectangular plate, whose length are more than one thousand times its width, so as to minimize the trim loss and the reduction of the times of clamping and changing speed are also concerned. This problem is different with the classical two-dimensional cutting problem. In view of the distinguishing features of the problem proposed, we put forward the definition of non-classical cutting, that is to say, put a series of items on the rectangular plates in their best layout, so as to enhance utility and efficiency at the same time. These objectives may be conflicting and a balance should be necessary, so we present a hybrid heuristic algorithm (HHA), consisting of clustering, ordering, striping and integer programming etc. We demonstrate the efficiency of the proposed algorithm through the comparison with the algorithm we studied before. (c) 2011 Elsevier Ltd. All rights reserved.

关键词： Non-classical cutting Steel coil cutting hybrid heuristic algorithm

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A hybrid heuristic algorithm for optimal energy scheduling of grid-connected micro grids

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ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS 2021年第4期12卷 877-893页

作者： Bektas, Zeynep Kayalica, M. Ozgur Kayakutlu, Gulgun Istanbul Univ Cerrahpasa Dept Ind Engn Istanbul Turkey Istanbul Tech Univ Dept Management Engn Istanbul Turkey Istanbul Tech Univ TEDRC Istanbul Turkey Istanbul Tech Univ Energy Inst Istanbul Turkey

The micro grids (MG) are small-scaled and restricted energy systems using distributed energy sources and storages. They can be operated in two different ways;grid-connected or islanded modes. The shifting between the modes depends on the volatility of demand. The use islanded mode is beneficiary as it helps minimizing the amount of power bought from main grid. It is not always possible unless a fertile field is found. This study proposes a hybrid heuristic approach for optimal management of MG considering regional conditions and constraints. For a power generating MG, the use of renewable resources in that region is as important as exchanging power with the main grid. MG is constructed in an industrial zone where the hourly power demand has to be matched. The aim is to schedule the power loads to minimize the amount of power taken from the main grid. To deal with this complex problem which contains power generation and consumption constraints, a versatile mathematical model must be established. The mathematical model needs to be integrated with a hybrid heuristic algorithm. Thus, a hybrid Genetic algorithm (GA)-Simulated Annealing (SA) method is proposed for solution. The schedule is programmed using GA, while, parameters are optimized by using SA. In the application stage, a MG in Gebze is simulated with three factories as consumers, where, grid connection and a wind turbine together with photovoltaic panels are assumed to be in use.

关键词： Energy load scheduling hybrid heuristic algorithm Optimal energy management Micro grid

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A hybrid heuristic algorithm for the Intelligent Transportation Scheduling Problem of the BRT System

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JOURNAL OF INTELLIGENT SYSTEMS 2015年第4期24卷 437-448页

作者： Zheng Ning Chen Tao Lin Fei Xu Haitao Hangzhou Dianzi Univ Xiasha Higher Educ Zone 215 Sixth Ave Hangzhou 310018 Zhejiang Peoples R China Hangzhou Dianzi Univ Hangzhou 310018 Zhejiang Peoples R China

This work proposes a hybrid heuristic algorithm to solve the bus rapid transit (BRT) intelligent scheduling problem, which is a combination of the genetic algorithm, simulated annealing algorithm, and fitness scaling method. The simulated annealing algorithm can increase the local search ability of the genetic algorithm, so as to accelerate its convergence speed. Fitness scaling can reduce the differences between individuals in the early stage of the algorithm, to prevent the genetic algorithm from falling into a local optimum through increasing the diversity of the population. It can also increase the selection probability of outstanding individuals, and speed up the convergence at the late stage of the algorithm, by increasing the differences between individuals. Using real operational data of BRT Line 1 in a city of Zhejiang province, the new scheduling scheme can be obtained through algorithm simulation. The passengers' total waiting time in a single way will be reduced by 40 h on average under the same operating cost compared with the original schedule scheme in a day.

关键词： hybrid heuristic algorithm intelligent scheduling BRT scheduling

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A two-storage multi-item inventory model with hybrid number and nested price discount via hybrid heuristic algorithm

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ANNALS OF OPERATIONS RESEARCH 2017年第1-2期248卷 281-304页

作者： Jana, Dipak Kumar Das, Barun Haldia Inst Technol Dept Appl Sci Haldia 721657 Purba Medinipur India Sidho Kanho Birsha Univ Dept Math Purulia 723101 W Bengal India

The purpose of this paper is to study a multi-item two warehouse inventory model with a nested discount on unit cost and inventory costs over a fixed time period. The concept of hybrid number and a new type of price discount have been applied in formulating an inventory control system having two separate storage facilities (owned-OW and rented-RW warehouses) due to limited capacity of OW. Here, demand rate is a linear function of selling price and time. The stocks at rented warehouse (RW) are transported to the owned warehouse (OW) following bulk-release rule. So, the mathematical model of the system becomes a constrained non-linear mixed-optimization problem. Here, taking the advantage of the randomness of multi-objective genetic algorithm with varying population (MOGAVP), for the first time, an algorithm has been proposed for the solution of multi-item two-warehouse inventory problems with nested price breaks. The optimum results are compared with MOGAVP and hybrid heuristic algorithm (HA). The optimal shipments, lot size of the two warehouses, shipment size and maximum profit are determined by maximizing the profit function. Finally optimal decision is made using above mentioned MOGAVP. Performance of the proposed MOGAVP on the model with respect to a standard MOGA and HA are compared.

关键词： Two-storage hybrid number K-release rule Nested discount Genetic algorithm hybrid heuristic algorithm

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Study on hybrid heuristic algorithm for Vehicle Routing Problem with Backhauls

Study on Hybrid Heuristic Algorithm for Vehicle Routing Prob...

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International Conference on Information Technology and Computer Science

作者： Ren Chunyu Sun Jinying Wang xiaobo Heilongjiang Univ Sch Informat Sci & Technol Harbin Peoples R China Building Energy Engn Ctr China Architecture Design & Res Grp China Building Design Consultants Beijing Peoples R China

ISBN: (纸本)9780769536880

In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with backhauls model. According to the characteristics of model, hybrid genetic heuristic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem;retain the best selection so as to guard the diversity of group. Improved ordinal crossover operators can avoid destroying good gene parts during the course of ordinal crossover so as that the algorithm can be convergent to the optimization as whole. Secondly, stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm to improve the convergent speed and searching efficiency of algorithm. The emulation and calculation proves that it is better than only using genetic algorithm and taboo searching algorithm.

关键词： VRPB hybrid genetic algorithm taboo searching algorithm hybrid heuristic algorithm

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BPSOBDE: A Binary Version of hybrid heuristic algorithm for Multidimensional Knapsack Problems 13

BPSOBDE: A Binary Version of Hybrid Heuristic Algorithm for ...

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13th International Conference on Computational Intelligence and Security (CIS)

作者： Zhang, Li Li, Hong Xidian Univ Sch Math & Stat Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)9781538648223

A hybrid heuristic algorithm, named BPSOBDE, is proposed for solving multidimensional knapsack problems (MKPs), in which the basic binary particle swarm optimization (BPSO) is combined with a binary differential evolution (BDE) to maintain the diversity of the swarm and makes it more explorative, effective and efficient. BPSOBDE is tested through computational experiments over suites of benchmark problems and the obtained results are compared with those of BPSO and some modified versions of BPSO. The experimental results show that BPSOBDE can successfully locate the exact solutions of all test problems. The comparison results indicate that BPSOBDE is a competitive heuristic algorithm.

关键词： Knapsack problems Binary particle swarm optimization Binary differential evolution hybrid heuristic algorithm

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A Dynamic Optimization Method of Intelligent Material Distribution Based on hybrid heuristic algorithm 9

A Dynamic Optimization Method of Intelligent Material Distri...

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9th International Conference on Industrial Technology and Management (ICITM)

作者： Cao Congcong Li Yueyu Wang Jiaojiao Sichuan Univ Business Sch Chengdu Peoples R China

ISBN: (数字)9781728143064

ISBN: (纸本)9781728143064

For the accuracy and timeliness of material distribution on the shop floor in uncertain environments, this paper constructs a dynamic material distribution method based on intelligent logistics technology under real-time monitoring of workshop. Based on the application of intelligent logistics technology, the real-time production progress monitored is taken as the basis to dynamically adjust the material delivery time window. A mathematical model is established to minimize the path cost, time window penalty cost and vehicle use cost, and a hybrid heuristic algorithm is designed to solve the problem. Finally, the effectiveness of the method is verified by an example of an automobile body production line. Compared with the traditional algorithm, the improved hybrid algorithm has more efficient optimization capability.

关键词： intelligent logistics dynamic mixing time window real-time monitoring hybrid heuristic algorithm

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STUDY ON hybrid heuristic algorithm FOR MULTI-DEPOT VEHICLE ROUTING PROBLEM WITH hybrid PICKING-DELIVERY STRATEGY

STUDY ON HYBRID HEURISTIC ALGORITHM FOR MULTI-DEPOT VEHICLE ...

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International Conference on Machine Learning and Cybernetics

作者： Wang, Xiao-Bo Sun, Jin-Ying Ren, Chun-Yu Heilongjiang Univ Sch Management Harbin 150080 Peoples R China Bldg Energy Engn Ctr China Architecture Design & Res Grp Beijing 100044 Peoples R China

ISBN: (纸本)9781424447053

With the rapid development of electronic commerce and logistics distribution, multi-depot vehicle routing problem with backhauls (MDVRPB) as influencing electronic commerce more step development, has been paid more attentions. According to the characteristics of model, hybrid heuristic algorithm is used to get the optimization solution. First of all, use hybrid coding so as to simplify the problem;construct the pertinence of initial solution to enhance the feasibility of solutions. Improved partially matched crossover operators can avoid destroying good gene parts during the course of crossover. According to the traditional genetic algorithm shortcomings of slowly convergent speed, the study adopts the strategy of protecting gene as whole, introduce adopts 2- exchange mutation operator. Secondly, stock elite adopting genetic algorithm with taboo searching algorithm to improve the convergent speed. This algorithm can offer the thought to settle the practical problem in scale. At the same time, it can be known that adopting hybrid picking-delivery strategy can save the distance of distribution route so as to improve economic benefit.

关键词： Vehicle routing problem with backhauls Stock elite Genetic algorithm Taboo searching algorithm hybrid heuristic algorithm

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