Dynamic Speed Optimization in Supply Chains with Stochastic Demand

Abstract

I n this paper, we analyze how to continuously adjust the speed in a supply chain with stochastic demand. For each unit (e.g., truckload, shipping container) in the chain, one must decide at which speed it should be moved downstream, given the state of the system, to minimize total supply chain costs. We decompose the problem into a set of one-dimensional subproblems that can be easily solved and characterize the optimal variable speed policy: under some assumptions, we show that it is optimal to set a speed that is first increasing in the distance to the market, and then decreasing. As a result, at optimality a given unit will experience an accelerating speed and then it will be slowed down, unless a demand occurs, in which case, the speed will be adjusted upward. We finally provide a transportation case study where we estimate the benefits of a variable-speed compared to a fixed-speed policy and show them to be significant both financially and from a CO 2 -emissions perspective.

Modeling and Engineering Constrained Shortest Path Algorithms for Battery Electric Vehicles

“…Although energy consumption can become negative, physical constraints prevent that cycles in the graph have negative energy consumption. In addition to that, the battery constraints mentioned above apply: If the battery of the EV has the SoC b u ∈ [0, M ] at some vertex u ∈ V , then traversing an arc (u, v) ∈ A results in the SoC (20,6) at v and a label (21,4) at t, which dominates the label (21,2) in the current set. (b) The initial SoC is 5.…”

“…Consequently, approaches in the literature (typically making use of mathematical programming and heuristics) do not scale to large, fully modeled road networks. Finally, we note that speed planning for vehicles is relevant not only in the context of route planning for EVs, but also in several other areas of transportation, such as supply chain management [20], aviation [89], or ship routing [69,72].…”

An Approximate Method for Integrated Stochastic Replenishment Planning with Supplier Selection

“…Those MSSPs can become intractable with increase in number of time periods and with increase in number of suppliers. Previous methods given in (Cheaitou and Van Delft, 2013), (Berling and Martínez-de Albéniz, 2015) and (Berling and Martínez-de Albéniz, 2016) consider demand distributions to be independent across time. In practice we often encounter dependent or correlated demand and distributions not following parametric distributions.…”

Responding to Shipment Delays: The Roles of Operational Flexibility & Lead‐Time Visibility

“…The strategy of using alternative suppliers and expediting shipment has been used in other contexts as well—most notably for mitigating the risk resulting from uncertainty in demand. For a detailed review of this literature, we refer readers to recent papers Janakiraman, Seshadri, and Sheopuri (), and Berling and Martínez‐de Albéniz () on these subjects. Finally, our article is also related to the body of empirical work that studies the impact of glitches in supply chain on a firm's financial performance—in this stream of work, Hendricks and Singhal () and Hendricks and Singhal (), respectively, illustrate the impact of supply chain glitches on the short‐ and long‐run stock performance, whereas Hendricks and Singhal () studies the impact of such events on a firm's operating income.…”