International Journal of Modelling in Operations Management (5 papers in press)
Developing the Mathematical Model for Hub Location Problem in line with Resistive Economy Approach
by Reza Ehtesham Rasi, Akram Ali Kazemi
Abstract: From the strategic managers' point of view, locating a hub facility with a structure based on maximizing flow and minimizing lost costs is an important part of the strategic decisions of the organization. This is because solving such problems has extensive applications in service systems including distribution, transportation, waste disposal, health services, emergency and telecommunications services. Hence, the purpose of locating service providers is to reduce costs and create appropriate conditions in the service network because of the wide variety of costs involved and great effects it has on managerial decisions. A review of past studies in this area suggests that these studies are mostly focused on a single goal. While the present study introduces a new problem in the field of hub location with a preventive reliability approach for transmitting the flow before hubs failure in which high reliability flow is released. Also, the present study uses the backup hub to allow correct flow passage after hubs failure to prevent the waste of flow due to hubs failure. Due to passing through the years of resistive economy, it is essential to design a mathematical model for the country's transport network in order to prevent the flow waste. Hence, a multi-objective mixed-integer programming model has been proposed for this problem and the weighted-sum approach has been utilized to solve it.
Keywords: hub location; reliability; backup hub; hub failure; resistive economy.
Genetic Algorithms for Task Assignments in Logistic Warehouses
by Zhaodong Wu, Min Wang
Abstract: By analysing the relevant elements in the allocation of storage tasks, a multi-objective storage task assignment model was built considering time and resource indicators and an improved genetic algorithm for this model is given and analysed through a case study. To assist warehouse managers in task scheduling, a desktop application for the storage task assignment was written in Java. The results showed that the improved genetic algorithm could accelerate the convergence speed and this model makes corresponding adjustments while the actual situation of the storage task changes. Compared with the task assignment scheme made through experience, the model not only reduces the time required but also the resources used
Keywords: assignment problem; logistics; warehouse task allocation; multi-objective model; genetic algorithm; NP problem.
The Intermediate Effects of Third-Party Payment Platform in China
by Weilun Huang, Xiaozhen Dai
Abstract: The purpose of this paper is to discuss the consumer behavior of third-party payment (TPP) in China, and the intermediate effects for the quality variables of TPP platform, which are its platform conveniences, applications conveniences, and social networks, from consumers perceived values and risks of TPP to the consumer TPP behavior. Furthermore, this paper tries to analyze the moderated effects of peoples gender, age and monthly income on their TPP behavior and the above intermediate effects. According to the results of a questionnaire survey in China and their statistical analysis, respondents' TPP behavior variables are their average TPP frequency is three times a day, and their average TPP amount is RMB 1,664 a month. It is found that the intermediate effects for the quality variables of TPP platform are significant. What is more, it is proven that the gender, age, and monthly income of people would moderate their TPP behavior and the intermediate effects for the application conveniences and social networks of TPP platform.
Keywords: Third-party Payment; Platform Convenience; Application Conveniences; Social Networks.
Retailer-led Supply Chain Contract Coordination with Supplier Group Evaluation
by Liu Liwei, Wang Luying, Wang Jingkun
Abstract: With the expansion of the enterprise scale, the original single supplier model has gradually evolved into a supplier group model. The evaluation of the retailer by the supplier group will have a certain impact on the retailer's decision. At the same time, as the status of retailers increases, retailers gradually grasp the dominance of the supply chain and use their channel advantages to charge channel cost to suppliers. Therefore, it is necessary to study the coordination problem of the supply chain when there is a supplier group's evaluation of the retailer and the retailer is dominant. This paper establishes the supply chain coordination decision model under the stackelberg game model, and finds that the wholesale price contract and the traditional revenue sharing contract cannot achieve the overall optimal supply chain. On this basis, this paper innovatively designed the ex ante contract - the improved revenue sharing contract to achieve supply chain coordination. And we compared this model with the traditional ex post contract - two-tariff contracts to provide guidance for retailers' contract choice. The results show that, firstly, the improved revenue sharing contract and the two-tariff contracts can achieve the coordination of the supply chain, and under the improved revenue sharing contract, the channel cost is smaller. Secondly, when the supplier group has a large evaluation coefficient for the retailer, even if the retailer charges only a low channel feel, it can still obtain high profits. Thirdly, under the two-tariff contracts, the retailer's profit decreases with the increase of the evaluation coefficient of the supplier group to the retailer. When the evaluation coefficient is large, the retailer should choose two-tariff contracts, and vice versa the retailer should choose the improved revenue sharing contract.
Keywords: Supplier group evaluation; Supply chain coordination; Revenue sharing contract; Two-tariff contracts.
Application of grey BP neural network in port logistics demand analysis
by Wei Xu, Nan Yu
Abstract: From the perspective of port cargo throughput, this paper first analyzes the characteristics and influencing factors of port logistics demand, and secondly considers the characteristics of logistics demand nonlinearity and small sample modeling. In the modeling process, GM(1,1) and BP neural network single prediction model are used for prediction. Then, according to the prediction result, the minimum square of the prediction error is used as the target, and the weight of the single model is given and the combined prediction model is constructed. Finally, taking the port of Qingdao as an example, the port logistics demand is simulated by MATLAB software. The results show that the combined forecasting model has higher precision and stability than the single forecasting model, which can effectively reduce the error rate and make the forecasting result closer. In fact, it has guiding significance for the future development of port logistics.
Keywords: GM(1,1); BP neural network; cargo throughput of port; logistics demand forecast;.