Optimization in inventory-routing problem with planned transshipment: A case study in the retail industry

Peres, Igor Tona; Repolho, Hugo M.; Martinelli, Rafael; Monteiro, Nathália Jucá

doi:10.1016/j.ijpe.2017.09.002

Cited by 55 publications

(27 citation statements)

References 20 publications

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“…Although, their research considered the assumption of a single product and single transportation mode, which need to be addressed, as in reality supply chain networks are quite complex as it deals with multiple product types and various transportation modes (Ge et al 2016). Although few researchers addressed some of the complex supply chain networks comprising of multi-period, multiproduct and multi-echelon (Soleimani et al 2013, Akbari et al 2015, Pasandideh et al 2015and Peres et al 2017. It has been observed that majority of the earlier published work overlooked the need to incorporate the decision making associated with the mode of transportation.…”

Section: Multi-period Multi-echelon Inventory Transportation Modelsmentioning

confidence: 99%

Multi-period multi-echelon inventory transportation problem considering stakeholders behavioural tendencies

Mogale

Zhang

et al. 2020

International Journal of Production Economics

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An inventory transportation problem of manufacturing organization focusing on several stakeholders such as manufacturers, distributors, wholesalers, retailers and customers is addressed in this paper. The research study considered multi-echelon, multi-product, multimodal and multi-period scenario. The mathematical model in the form of mixed integer nonlinear programming is formulated to minimize the total cost associated with transportation, inventory holding and operational activities. A mathematical formulation based heuristic approach, which comprises of four algorithms, is proposed for solving purpose. The proposed heuristic approach considers the behavioural tendencies of stakeholders pertaining to the selection of shipment routes, transportation mode choice decisions and amount of products to be shipped. Fifteen practical problem instances are solved by using the developed heuristic approach while considering the behavioural aspects of stakeholders. Insights obtained from results will be beneficial for manufacturing organizations in making informed decisions related to transportation planning considering stakeholder's behavioural tendencies.

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Section: Multi-period Multi-echelon Inventory Transportation Modelsmentioning

confidence: 99%

Multi-period multi-echelon inventory transportation problem considering stakeholders behavioural tendencies

Mogale

Zhang

et al. 2020

International Journal of Production Economics

View full text Add to dashboard Cite

show abstract

“…In this paper, we deal with an exact dynamic programming approach. For some further recent general approaches for the solution of different types of single and multiple criteria scheduling problems, the interested reader is referred to [23][24][25][26][27][28][29] which highlight the importance of developing advanced scheduling approaches. This concerns both the identification of new polynomially solvable problems as well as new MILP models and metaheuristic or hybrid algorithms.…”

Section: Literature Overviewmentioning

confidence: 99%

Two-Machine Job-Shop Scheduling with Equal Processing Times on Each Machine

Gafarov

Werner

2019

Mathematics

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In this paper, we consider a two-machine job-shop scheduling problem of minimizing total completion time subject to n jobs with two operations and equal processing times on each machine. This problem occurs e.g., as a single-track railway scheduling problem with three stations and constant travel times between any two adjacent stations. We present a polynomial dynamic programming algorithm of the complexity O ( n 5 ) and a heuristic procedure of the complexity O ( n 3 ) . This settles the complexity status of the problem under consideration which was open before and extends earlier work for the two-station single-track railway scheduling problem. We also present computational results of the comparison of both algorithms. For the 30,000 instances with up to 30 jobs considered, the average relative error of the heuristic is less than 1 % . In our tests, the practical running time of the dynamic programming algorithm was even bounded by O ( n 4 ) .

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“…A novel heuristic algorithm, which accounts for the truck service priority and the truck service order restrictions, was proposed for initializing the chromosomes and population [23]. Peres et al [24] presented an exact formulation and developed a metaheuristic to solve a multi-period, multi-product Inventory-Routing Problem. A Memetic Algorithm was developed to minimize the total vessel service cost for the vessel diversion decision making [25].…”

Section: Related Workmentioning

confidence: 99%

Stream Data Load Prediction for Resource Scaling Using Online Support Vector Regression

Kang

Zheng

2019

Algorithms

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A distributed data stream processing system handles real-time, changeable and sudden streaming data load. Its elastic resource allocation has become a fundamental and challenging problem with a fixed strategy that will result in waste of resources or a reduction in QoS (quality of service). Spark Streaming as an emerging system has been developed to process real time stream data analytics by using micro-batch approach. In this paper, first, we propose an improved SVR (support vector regression) based stream data load prediction scheme. Then, we design a spark-based maximum sustainable throughput of time window (MSTW) performance model to find the optimized number of virtual machines. Finally, we present a resource scaling algorithm TWRES (time window resource elasticity scaling algorithm) with MSTW constraint and streaming data load prediction. The evaluation results show that TWRES could improve resource utilization and mitigate SLA (service level agreement) violation.

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Optimization in inventory-routing problem with planned transshipment: A case study in the retail industry

Cited by 55 publications

References 20 publications

Multi-period multi-echelon inventory transportation problem considering stakeholders behavioural tendencies

Multi-period multi-echelon inventory transportation problem considering stakeholders behavioural tendencies

Two-Machine Job-Shop Scheduling with Equal Processing Times on Each Machine

Stream Data Load Prediction for Resource Scaling Using Online Support Vector Regression

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