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9th IEEE International Conference on Computer Science and Education (ICCSE)

作者： Pan Ling Sun Ying Wei Ningbo Dahongying Univ Coll Informat Engn Ningbo Zhejiang Peoples R China

ISBN: (纸本)9781479929511

Vehicle scheduling problem in distribution step has always been the focus of domestic and overseas academic circles. Especially during recent years, with rising of logistics as a new industry, optimization of vehicle scheduling has become a hot issue. Optimization for vehicle scheduling in distribution step can not only save cost and improve economic returns for enterprises, but is also beneficial to realizing scientific logistics management. At present, there are many algorithms involved in vehicle scheduling and this paper chose two typical algorithms - traditional heuristics algorithm and genetic algorithm;characteristics of these two algorithms were discussed. Finally through comparison, it pointed out how to choose proper algorithm in solving practical problems.

关键词： vehicle scheduling problem heuristics algorithm genetic algorithm

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Vehicle Routing Problem Based on Object-oriented Discrete Event Simulation

Vehicle Routing Problem Based on Object-oriented Discrete Ev...

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2nd IEEE International Conference on Advanced Computer Control

作者： Sun Zhongyue Guan Zhongliang Beijing Jiaotong Univ Sch Econ & Management Beijing Peoples R China

ISBN: (纸本)9781424458479

A new solution to vehicle routing problem (VRP) is proposed in order to overcome the disadvantages that the exact algorithms and heuristics algorithms are difficult to solve vehicle routing problem with multiple constraints. A simulation model of vehicle routing problem is built by combining the object-oriented technology and discrete event simulation technology. In this model, the events of distribution process and resources are described by the object-oriented approach. A variety of constraints which VRP problem involves can be processed in the simulation. As a result, the model has truly simulated complicated vehicle distribution process and simulation results can provide a basis for various optimization algorithms. The experimental results have validated the feasibility and effectiveness of this new method. As the simulation results can document the whole distribution process in detail, this method will have some significance to the practical application of vehicle routing problem.

关键词： object-oriented discrete event simulation vehicle routing problem heuristics algorithm

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Optimization Approach for Multi-stork Inventory Routing Problem

Optimization Approach for Multi-stork Inventory Routing Prob...

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International Conference on Computational Materials Science (CMS 2011)

作者： Lei, Juncheng Wu, Yanpeng Zeng, Wenfei Shaoyang Univ Dept Informat Engn Shaoyang 422000 Hunan Peoples R China

ISBN: (纸本)9783037851555

Inventory routing problem is one of the key issues to achieve integrated management of logistics. Solving this problem effectively, we can improve vehicle utilization, and reduce distribution costs. This paper, concerning the problem in inventory routing of multi-variety, multi-vendor to multi-customers, proposed heuristic algorithm based on greedy rules. The core strategy of the algorithm is to choose circularly the current lowest unit cost routine -Hamilton delivery routes. Simulation shows that the algorithm reduces the unloaded ratio of truck, raises the efficiency of truck delivery and saves transport costs.

关键词： inventory routing problem integrated logistics management heuristics algorithm greedy algorithm

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A Novel algorithm for Solving Cutting Tool Path Generation

A Novel Algorithm for Solving Cutting Tool Path Generation

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International Conference on Information Science, Electronics and Electrical Engineering (ISEEE)

作者： Li, Xun Chen, Ming Harbin Inst Technol Shenzhen Peoples R China

ISBN: (纸本)9781479931972

Based on MAX-MIN Ant System (MMAS), we proposed a novel algorithm to minimize the idle traveling of tool path on cutting 2D intensive multi-contour patterns. The proposed algorithm consists of four steps: 1) use standard MMAS algorithm to define the pattern order;2) seek the appearing node according to the pattern order;3) optimize the node sequence with MMAS algorithm;4) repeat the step 2) and 3) to achieve the optimal tool path. Experiments show that the proposed algorithm can effectively generate optimal tool path and obtains a noticeable advantage against the line-scanning algorithm and NACS algorithm.

关键词： MAX-MIN Ant System tool path heuristics algorithm intensive multi-contour patterns

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Finding a Wise Group of Experts in Social Networks

Finding a Wise Group of Experts in Social Networks

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7th International Conference on Advanced Data Mining and Applications

作者： Yin, Hongzhi Cui, Bin Huang, Yuxin Peking Univ Dept Comp Sci Beijing 100871 Peoples R China Peking Univ Key Lab High Confidence Software Technol Beijing 100871 Peoples R China

ISBN: (纸本)9783642258527

Given a task T, a pool of experts x with different skills, and a social network G that captures social relationships and various interactions among these experts, we study the problem of finding a wise group of experts chi', a subset of x, to perform the task. We call this the Expert Group Formation problem in this paper. In order to reduce various potential social influence among team members and avoid following the crowd, we require that the members of chi' not only meet the skill requirements of the task, but also be diverse. To quantify the diversity of a group of experts, we propose one metric based on the social influence incurred by the subgraph in G that only involves chi'. We analyze the problem of Diverse Expert Group Formation and show that it is NP-hard. We explore its connections with existing combinatorial problems and propose novel algorithms for its approximation solution. To the best of our knowledge, this is the first work to study diversity in the social graph and facilitate its effect in the Expert Group Formation problem. We conduct extensive experiments on the DBLP dataset and the experimental results show that our framework works well in practice and gives useful and intuitive results.

关键词： team formation social influence social network heuristics algorithm

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Research and Design of Task Scheduling Method Based on Grid Computing 2

Research and Design of Task Scheduling Method Based on Grid ...

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2nd International Conference on Smart City and Systems Engineering (ICSCSE)

作者： Feng, Liu Guo Wei-wei Heilongjiang Univ Technol JiXi 158100 Peoples R China

ISBN: (纸本)9781538614013

algorithm research of task scheduling is one of the key techniques in grid computing. This paper firstly describes an DAG task scheduling model used in grid computing environment, then discusses generational scheduling (GS) and communication inclusion generational scheduling (CIGS) algorithms. Finally, an improved CIGS algorithm is proposed to use in grid computing environment, and it has been proved effectively.

关键词： Grid Computing Model of Task Scheduling heuristics algorithm Dependent Task Scheduling algorithm

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Case Study Analysis of Job Shop Scheduling and its Integration with Material Requirement Planning

Case Study Analysis of Job Shop Scheduling and its Integrati...

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International Conference on Advances in Materials, Manufacturing and Applied Sciences (ICAMMAS)

作者： Ramya, G. Chandrasekaran, M. Shankar, E. Rajalakshmi Engn Coll Dept Mech Engn Chennai 602105 Tamil Nadu India Vels Univ Dept Mfg Engn Chennai 600025 Tamil Nadu India

Now a days, an integrated manufacturing environment is essential in modem manufacturing industries. To achieve truly integrated manufacturing systems, the integration of Material Requirements Planning (MRP) and job shop is essential. In the job shop scheduling problem n jobs have to be processed on m different machines and each job consists of a sequence of tasks that have to be processed during a fixed length on a given machine for an uninterrupted time period. In this work, enterprise application framework for integrating MRP with job shop scheduling is developed. This integrated system consists of two modules. First module provides a common material representation for material requirement planning and scheduling to tackle the variability in job durations and machine allocations. The second model provides an integrated heterogeneous manufacturing facilities with feasible production schedule. At the first stage, the application accepts the customer's order and performs material requirement planning. Further the master production schedule dispatches the daily planned order with all production resource requirement to job shop. At the same time, MRP sends order to supplier for purchasing raw materials. Shuffled Frog Leaping algorithm (SFL) is used to find an optimum schedule as well as refine the makespan results. Once the customers add or modify orders, MRP system will update the resource data automatically and respond to the changes of customer requirements rapidly. In this integrated application, the MRP subsystem has been proposed to computerize the existing system with *** and MYSQL Server to perform Business-to-Customer transactions and MRP logic, while the job shop simulator generates different sequences randomly and using Gantt chart initial makespan was calculated. Initial solutions refined with SFL algorithm and optimum schedule is generated. MYSQL Server Module is used for integrating MRP with Job shop simulator using Visual Basic. NET as the front end a

关键词： Material Requirement Planning Job shop simulator Integration heuristics algorithm SFL algorithm

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A two-stage sustainable uncertain multi-objective portfolio selection and scheduling considering conflicting criteria

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 132卷

作者： Ramedani, Amir Mohammad Mehrabian, Ahmad Didehkhani, Hosein Islamic Azad Univ Dept Ind Engn Aliabad Katoul Branch Aliabad Katoul Iran

This article presents a pioneering approach to project portfolio selection and scheduling, addressing the complexities of contemporary decision-making environments characterized by uncertainty, conflicting criteria, and sustainability imperatives. The proposed framework integrates multiple-attribute and multiple-objective decision-making methods, offering a two-stage solution incorporating fuzzy-robust-stochastic (FRS) optimization techniques. Notably, our work introduces a novel heuristics algorithm designed to optimize conflicting criteria related to sustainability, time-dependency, resources, budget constraints, and human resource capabilities. In the first stage, the framework employs advanced multiple-attribute decision-making methods to comprehensively evaluate project portfolios under the influence of diverse and conflicting criteria. Subsequently, the second stage employs sophisticated multiple-objective decision-making methods to refine the portfolio selection by considering fuzzy, robust, and stochastic optimization elements. The introduced heuristics algorithm plays a pivotal role in enhancing the efficiency and effectiveness of the decision-making process, providing a robust solution to the intricate challenges posed by sustainability concerns, temporal dependencies, resource constraints, budget limitations, and human resource capabilities. The innovation lies in the integration of these disparate elements into a cohesive, two-stage framework, which not only ensures the optimal selection of portfolios but also holistically addresses the intricacies of scheduling. Applying FRS optimization in tandem with the novel heuristics algorithm sets this work apart, offering a versatile and comprehensive solution to decision-makers facing the multifaceted challenges of contemporary project management. Finally, different sensitivity analyses on the proposed model and evaluations of the solution algorithm in various test problems highlight the flexibility of the mode

关键词： Sustainability Project portfolio selection heuristics algorithm Conflicting criteria Scheduling Multiple-attribute decision-making Multiple-objective decision-making

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Model and algorithm for container ship stowage planning based on bin-packing problem

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Journal of Marine Science and Application 2005年第3期4卷 30-36页

作者： ZHANG Wei-ying LIN Yan JI Zhuo-shang Ship CAD Engineering Centre Dalian University of Technology Dalian 116024 China College of Marine Engineering Dalian Fisheries University Dalian 116023 China

In a general case, container ship serves many different ports on each voyage. A stowage planning for container ship made at one port must take account of the influence on subsequent ports. So the complexity of stowage planning problem increases due to its multi-ports nature. This problem is NP-hard problem. In order to reduce the computational complexity, the problem is decomposed into two sub-problems in this paper. First, container ship stowage problem (CSSP) is regarded as 'packing problem', ship-bays on the board of vessel are regarded as bins, the number of slots at each bay are taken as capacities of bins, and containers with different characteristics (homogeneous containers group) are treated as items packed. At this stage, there are two objective functions, one is to minimize the number of bays packed by containers and the other is to minimize the number of overstows. Secondly, containers assigned to each bays at first stage are allocate to special slot, the objective functions are to minimize the metacentric height, heel and *** taboo search heuristics algorithm are used to solve the subproblem. The main focus of this paper is on the first subproblem. A case certifies the feasibility of the model and algorithm.

关键词： container ship stowage bin-packing problem heuristics algorithm

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Multi-echelon sustainable reverse logistics network design with incentive mechanism for eco-packages

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JOURNAL OF CLEANER PRODUCTION 2023年 430卷

作者： Zhou, Ji Yang, Senyan Feng, Hui An, Zexu Beijing Univ Posts & Telecommun Sch Modern Post Sch Automat Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Sch Comp Sci Beijing 100876 Peoples R China

With the pollution caused by express packaging waste, eco-packages are being commonly used to promote a green supply chain. However, extant research has yet to address the efficacious reverse logistics network design problem while considering both economic and environmental consumption in the recycling process. In this study, a multi-echelon reverse logistics network is designed to collect eco-packages from customers, instead of door-todoor recycling by couriers. This study aims to solve the capacity location-routing problem in a reverse logistics network integrated with the incentive mechanism for customers, which is regarded as NP-hard. To avoid the combinatorial explosion, a multi-objective hybrid genetic algorithm-tabu search (MOHGATS) is developed to reduce search space and improve search speed by changing search strategies. Computational experiments are conducted to verify the proposed model and algorithm based on several test instances and a real-world case study. The impacts of the quantity of eco-packages, the incentive costs for customers, and the quantity and capacity of recycling stations on the reverse logistics network are explored from both economic and environmental perspectives, providing a reference for practical operation and promotion of eco-packages on a large scale.

关键词： Eco-packages Green reverse logistics Location-routing problem Incentive mechanism Multi-objective optimization heuristics algorithm

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