## 1 Introduction  
In temporal freight (shipment) consolidation, small orders are aggregated over time in the consolidation center to make bigger shipments to the customer (retailer) [1]. This is in addition to product-based consolidation in which products from several suppliers are aggregated to be delivered for the same customer [2]. A sustainable supply chain is about the achievement of an organization's social, environmental, and economic goals. These goals are supportive for the organization and the community. Reducing the number of shipments and using larger shipments contributes to decreasing the traffic jam as one of the social benefits. The environmental effect is attained by reducing the CO\({}_{2}\) emissions by reducing the number of shipments [3]. The economic goal is accomplished by reducing transportation costs. This is achieved as long as the savings are larger than the increase in inventory holding costs and as long as the lead time is not strongly affected. Moreover, consolidation reduces the number of vehicles and the size of the workforce needed. This is important in the time of the COVID-19 pandemic, where a shortage in the workforce in logistics is a big problem. Moreover, it will be useful for customers because they will have a lower number of shipments, and therefore, lower handling costs. All these three goals of sustainability and the response to COVID-19 are some of the motivations for this study. In addition, this study is the first one that considers temporal consolidation as the objective for forecasting. However, temporal consolidation is only performed if there is a good chance that other orders for the same customer will come in the few coming days, where the waiting period is much smaller than the average lead time (time elapsed between making the order by the customer and receiving the order on the warehouse) [4]. Therefore, accurate forecasting of orders lead time is needed. Lead-time forecasting is an extremely challenging task [5]. The variability in production lead time can be due to factors such as machine breakdown and maintenance [6]. Predicting longer lead times is more difficult and tends to be less accurate because uncertainty leads to an increase in the variance of estimation [7]. Instead of making traditional static forecasting for each order, dynamic forecasting is performed in this paper, where the evaluation is recalculated after each delivery or each demand [8]. This research is inspired by a case study of a furniture design company, which makes designs and sells products. The company outsources all the manufacturing activities to external suppliers in the east of Europe, where customers of the company are mainly in the west of Europe. The company follows this strategy to utilize the low manufacturing costs in the east of Europe. There are more than 1000 customers (retailers) spread in several countries in the west of Europe. Most of the demand by each customer is usually one or a few pallets. One order by a customer might include items from several suppliers at the same time. To aggregate the small orders together, a consolidation center (large warehouse) is needed in the west of Europe to put the needed items for each group of customers in the same small zone on the same truck to reduce transportation costs. This strategy is called a milk run. The warehouse is managed by a third-party logistics provider (3 PL). This case study is similar to those described in [PERSON] et al. [4; 9]. However, the objectives in this paper are different. The general aim of this paper is to make forecasting that satisfies the company's special needs of reducing the total costs by temporal consolidation. That means that forecasting is an input for the temporal consolidation plan, in which aggregating larger shipments is performed. To plan that, a special type of forecasting with binary results (come, not come) is needed. Instead of evaluating the exact lead time for each order, the manager is interested more in the probability of the arrival of the order in the next delivery week.