## 2 Literature Review
Meanwhile, in this paper, we propose an integrated decision making process that shares information (e.g., the purpose of each stakeholder) through cooperation between stakeholders and benefits all stakeholders. In the broad context of competition between transport chains, a dry port is an extended version of a seaport [17; 18]. In particular, since ports affect the competitive advantage of the hinterland [19], inland distribution is an important factor [20]. The dry ports are far fromtypical borders but have access to major metropolitan areas, highways, and labor bases [21]. From a functional perspective, the dry ports consist of close, mid-range, and distant dry ports [18]. Therefore, the TAS of this paper is available to a dry port as well as a seaport. Most previous studies have focused only on strategies for determining truck schedules that can reduce the turnaround time from the perspective of the transport company (forwarder). From the perspective of the terminal operator, they have focused only on strategies for determining yard crane operations that can improve the productivity of the container terminal. This paper differs from previous studies in the following aspects:  
1. As a factor in reducing truck turnaround time from the perspective of the transport company (forwarder), most of the previous studies only considered truck waiting time, which did not reflect container rehandling time. However, this paper covers not only truck waiting time but container rehandling time as well. In this way, this paper can express truck turnaround time in more detail. 2. As a factor for improving terminal productivity from the perspective of the terminal operator, most previous studies only considered workload balancing and distribution containers to each yard block. However, this paper not only considers workload balancing but also reduces the waste of resources by increasing the number of available and reserved slots together. In this way, this paper can more directly express terminal productivity. 3. Previous studies of the negotiation process between the transport companies (forwarders) and the terminal operator required a sequential decision making process of exchanging their own decisions. However, in this paper we develop a mathematical model for integrated decision making that considers the transport companies (forwarders) and the terminal operator at the same time. Furthermore, it compares the results of numerical experiments for cases where transport companies (forwarders) and terminal operator make their own decisions and cooperate. Then we propose a model that benefits all stakeholders. For example, we suppose there are one-yard block and two-time windows (\(t_{1}\) and \(t_{2}\)) for two transport companies (forwarders). In the sequential decision making process, each company allocates trucks by time window without information from each other. (Company A: five trucks for time window; Company B: four trucks for time window \(t_{1}\) and two trucks for time window \(t_{2}\)). There are nine trucks for time window \(t_{1}\) and two trucks for time window \(t_{2}\). Then, the terminal operator informs each company that congestion will occur due to a longer turnaround time in time window \(t_{1}\). Therefore, each company decides to move the two trucks from the time window \(t_{1}\) to time window \(t_{2}\). (Company A: three trucks for time window \(t_{1}\) and two trucks for time window \(t_{2}\); Company B: two trucks for time window \(t_{1}\) and four trucks for time window \(t_{2}\)). Finally, the terminal operator informs each company that congestion is unlikely to occur. On the other hand, the integrated decision making process proposed in this study considers cooperation between transport companies (forwarders) and the terminal operator so they share their information. Company A should allocate trucks to time window \(t_{1}\) as much as possible, and company B does not have a problem with either time window \(t_{1}\) or time window \(t_{2}\).