Effect of Additional Order in Two-Stage Supply Chain Contract under the Demand Uncertainty

Chueanun, Suphannee; Suwandechochai, Rawee

doi:10.3390/computation9030037

Cited by 3 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Distribution planning problems with stochastic and time-dependent travel times with time-varying temperatures were modelled [20,[29][30][31]. Chueanun and Suwandechochai [32], Derigs et al [33], Mendoza et al [34] and Reis and Leal [35] proposed different shipping strategies, different numbers of actors in the transportation chain and different limitations of the transportation modes. In our study, the transportation time was (the time from the origin to the destination) needed to be within a certain limit.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Artificial Multiple Intelligence System (AMIS) for Agricultural Product Transborder Logistics Network Design in the Greater Mekong Subregion (GMS)

et al. 2022

View full text Add to dashboard Cite

In recent years, agriculture products have contributed to 28.75% of Thailand’s GDP. China, Vietnam, Myanmar, Cambodia, Laos and Vietnam are the main markets for agricultural products. The annual export volume exceeds 119,222 million THB. The majority of them are shipped over Thailand’s land borders to its neighbors. Small and medium-sized farmers make up more than 85% of those who produce agricultural items. Numerous scholars have studied the transportation methods used by the Greater Mekong Subregion (GMS) nations along the economic corridor, but the majority of them have concentrated on import–export operations involving sizable firms, which are not applicable to the transportation of agricultural products, particularly when attention is paid to small and medium-sized farmers. In this study, mixed-integer programming (MIP) is presented to design an agricultural product logistics network. In order to prolong the lifespan of the container used, the MIP’s primary goal is to maximize the total chain profit while maintaining the lowest container usage possible. The approach was developed to increase small and medium-sized farmers’ ability to compete. Small and medium-sized farmers bring their products to an agricultural product collecting center, also known as a container loading facility. After that, skilled logistics companies distribute the goods. In order to convey the goods to the final clients in neighboring nations, the proper locations of the containing loading centers, the correct transportation option and the borders must be decided. The issue was identified as multi-echelon location–allocation sizing (MELLS), an NP-hard problem that cannot be handled in an efficient manner. To solve a real-world problem, however, efficient techniques must be supplied. AMIS, an artificial multiple intelligence system, was created to address the suggested issue. AMIS was developed with the goal of leveraging a variety of methods for local search and development. There are several well-known heuristics techniques employed in the literature, including the genetic algorithm (GA) and the differential evolution algorithm (DE). With respect to the improved solutions obtained, the computational results show that AMIS exceeds the present heuristics, outperforming DE and GA by 9.34% and 10.95%, respectively. Additionally, the system’s farmers made a total of 15,236,832 THB in profit, with an average profit per container of 317,434 THB and an average profit per farmer of 92,344.44 THB per crop. The container loading center uses 48 containers, with a 5.33 container average per container loading center (CLC). The farmers’ annual revenues were previously less than 88,402 THB per family per year, so we can predict that the new network may increase customers’ annual income by 4.459% for each crop.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

“…The results for the profit per container of each weight are shown in Table 15. The objective function was modified to create Equations ( 31) and (32).…”

Section: The Amis's Effectivenessmentioning

confidence: 99%

A Novel Artificial Multiple Intelligence System (AMIS) for Agricultural Product Transborder Logistics Network Design in the Greater Mekong Subregion (GMS)

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Until the borrower repays, the item is always in seizure and cannot be taken out of the warehouse, nor is it allowed to be replaced. The dynamic pledge means that after the pledge is transferred to the warehouse under the supervision of the logistics enterprise, the pledgor can use the replacement pledge that meets the contract requirements according to its own business needs, so as to realize the transaction operation of the goods [ 24 , 25 ]. The supply chain structure of core business activities is shown in Figure 1 .…”

Section: Internet Of Things and Supply Chain Financementioning

confidence: 99%

An Intelligent Supervision for Supply Chain Finance and Logistics Based on Internet of Things

Bai

Liu

Wang

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Supply chain finance and logistics activities are developing rapidly. In the economic activities of the tripartite cooperation between financial institutions, logistics enterprises, and loan enterprises, the goods will enter the logistics and supervision links of pledged goods immediately after they are postponed. It is proposed to integrate computer network communication technologies such as the Internet of Things with supply chain finance and logistics supervision to strengthen the information interaction between suppliers, which is widely used in supply chain activities to help realize the Internet finance. An intelligent supply chain supervision can implement monitoring and early warning of the time of the pledged goods in the warehouse, in transit, and during processing. Therefore, this paper proposes an intelligent supply chain supervision model by integrating supply chain finance, logistics, and pledge finance models into an operation management platform to better promote the smooth progress of supply chain finance and logistics supervision activities, which can effectively reduce various external risks, improve operational efficiency, and provide reference for supply chain finance and logistics activities.

show abstract

Modification of the Bellman–Ford Algorithm for Finding the Optimal Route in Multilayer Network Structures

et al. 2023

View full text Add to dashboard Cite

One of the actual tasks of the contemporary logistics business using the “just in time” supply planning concept, is to distribute manufactured goods among the objects of the distribution network in the most efficient manner at the lowest possible cost. The article is devoted to the problem of finding the optimal path in network structures. The problem statement for multilayer data transmission networks (MDTN), which is one of the possible representations of multimodal transport networks, is considered. Thus, each MDTN layer can be represented as a separate type of transport. The problem is solved by modifying the Bellman–Ford mathematical programming algorithm. Load testing of the modified method was performed, and a comparative analysis was given, including an assessment of speed and performance, proving the effectiveness of the results of the study. Based on the results of comparative analysis, recommendations for using a modified version of the Bellman–Ford algorithm for application in practical problems in optimizing logistics networks are proposed. The results obtained can be used in practice not only in logistics networks but also in the construction of smart energy networks, as well as in other subject areas that require optimization of multilayer graph structures.

show abstract

Effect of Additional Order in Two-Stage Supply Chain Contract under the Demand Uncertainty

Cited by 3 publications

References 14 publications

A Novel Artificial Multiple Intelligence System (AMIS) for Agricultural Product Transborder Logistics Network Design in the Greater Mekong Subregion (GMS)

A Novel Artificial Multiple Intelligence System (AMIS) for Agricultural Product Transborder Logistics Network Design in the Greater Mekong Subregion (GMS)

An Intelligent Supervision for Supply Chain Finance and Logistics Based on Internet of Things

Modification of the Bellman–Ford Algorithm for Finding the Optimal Route in Multilayer Network Structures

Contact Info

Product

Resources

About