Dynamic Vehicle Routing Problem—Predictive and Unexpected Customer Availability

Kucharska, Edyta

doi:10.3390/sym11040546

Cited by 17 publications

(8 citation statements)

References 39 publications

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“…Sentiment analysis can be used especially to improve the accuracy of demand forecasting. For future work, the proposed method can be also applied to other problems, such as the dynamic vehicle routing problem [43] and dual-channel supply chain [44].…”

Section: Discussionmentioning

confidence: 99%

A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem

et al. 2019

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In this paper, a new hybrid method including simulation optimization and artificial intelligence based simulation is created to solve the inventory routing problem (IRP) in which three different routing strategies are evaluated for uneven demand patterns including intermittent, erratic, and lumpy demand. The proposed method includes two phases. In the first phase, a nondominated sorting genetic algorithm II based simulation is employed to perform a multi-objective search for the IRP where the objectives of the method are total supply chain cost minimization and average service level maximization. In the second phase, artificial neural network based simulation is used to adjust the reorder point and order-up-to-level by forecasting the customer demand at each replenishment time. The results of the study demonstrated that the average service level is at least 98.54% in the supply chain. From this, it can be concluded that the proposed method can provide a tremendous opportunity to improve the average service level under uncertain environments. In addition, it is determined that different routing strategies can be selected for different demand patterns according to the considered performance measures.

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Section: Discussionmentioning

confidence: 99%

A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem

et al. 2019

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“…This is a different approach than the typical queuing scheduling system. Moreover, as shown by Kucharska (2019) instead of only using information about currently available jobs or machines, ALMM can include additional information about the expected availability in the future. In such a case time can be calculated based on the given rules and restrictions of the problem or predicted based on historical data.…”

Section: Predictive Schedulingmentioning

confidence: 99%

Formal Scheduling Method for Zero-Defect Manufacturing

Grobler-Dębska

Kucharska

Baranowski

2021

Preprint

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Zero-defect manufacturing (ZDM) is a concept of quality management that recently exhibits a renewal of interest. It aims to improve the process efficiency and the product quality while eliminating defects and minimizing process errors. Most of ZDM applications focus on using the technological achievements of Industry 4.0 to detect and predict defects, forgetting to optimize the schedule on the production line. This paper proposes a formal approach for solving scheduling problems with unexpected events as extension of general frameworks for ZDM strategy. We propose formal method to create predictive-reactive schedule for problems with defect detection and repair. Our formal model combines defect detection, heuristics construction and decision support. We illustrate our results with examples.

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“…Zeng et al developed a comprehensive model based spherical fuzzy rough set model hybrid with TOPSIS (technique for order preference by similarity to ideal solution) for multi-attribute decision making regarding human opinions [21]. Kucharska proposed a classification of the dynamic vehicle routing problem (DVRP) due to various elements causing dynamism to distinguish dynamic vehicle routing problems, which takes into account the dynamic appearance of customers to serve during the design or execution of the routes [22]. These decision problems are usually solved by applying a multi-standard decision-making (MCDM) framework wherein decisions are built by considering multiple standards or perspectives.…”

Section: Symmetric Decision-makingmentioning

confidence: 99%

“…Considering the distribution and symmetry of the planning and decision-making processes in the shipbuilding projects, an appropriate decision-making method and tool to assist the participants to make better decisions is extremely important. There are many researches on symmetric decision-making theory, including the decision-making model [19][20][21][22][23] and decision-making system modeling [24][25][26][27][28][29]. The purpose of this paper is to provide effective decision-making methods for project participants.…”

Section: Introductionmentioning

confidence: 99%

Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment

Mao

Guo

et al. 2020

Symmetry

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In the current distributed manufacturing environment, more extensive enterprise cooperation is an effective means for shipbuilding companies to increase the competitiveness. However, considering the project scale and the uneven production capacity between the collaborative enterprises, a key issue for shipbuilding companies is to effectively combine the product-oriented project tasks and the specialized production-oriented plants. Due to information privatization, the decision-making process of project planning and scheduling is distributed and symmetric. Existing project scheduling methods and collaboration mechanisms in the shipbuilding industry are somehow inefficient. The aim of the research is to provide an assistant decision-making method to support effective task dispatching and multi-party cooperation for better utilization of the distributed resources and to help project managers control the shipbuilding process. The article initially establishes an agent-based complex shipbuilding project collaborative planning and symmetric scheduling framework, simulating the distributed collaborative decision-making process and bridging the multi-project planning with the individual project scheduling in much detail, which fills the research gap. A negotiation method based on iterative combination auction (ICA) is further proposed to solve the integration problem of project planning and task scheduling, and an illustrative example is conducted to demonstrate the effectiveness and rationality of the methods. Finally, an application case using a prototype system on shipbuilding projects collaborative planning and scheduling will be reported as a result.

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Dynamic Vehicle Routing Problem—Predictive and Unexpected Customer Availability

Cited by 17 publications

References 39 publications

A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem

A Novel Hybrid Artificial Intelligence Based Methodology for the Inventory Routing Problem

Formal Scheduling Method for Zero-Defect Manufacturing

Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment

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