Decision Support for Consumer Direct Grocery Initiatives

Abstract

Many companies with consumer direct service models, especially grocery delivery services, have found that home delivery poses an enormous logistical challenge due to the unpredictability of demand coupled with strict delivery windows and low profit margin products. These systems have proven difficult to manage effectively and could benefit from new technology, particularly to manage the interaction between order capture and promise and order delivery. In this paper, we define routing and scheduling problems that capture important features of this emerging business model and propose algorithms, based on insertion heuristics, for their solution. The emphasis is on profit maximization. The vendor has to decide which requests to accept and in which time slot to guarantee delivery, for those that are accepted. Computational experiments demonstrate the importance of an integrated approach to order capture and promise and order delivery and the quality and value of the proposed algorithms. 3 Literature Research is emerging that analyzes routing strategies for unattended home deliveries where time slots are not of concern. In (Punakivi 2000), the routing options studied include the use of fixed routes and the optimal sequencing of the deliveries on routes as soon as all deliveries are known. The results demonstrate the importance of optimization in CD with savings from optimal routing

Consumer-driven e-commerce

“…• Product margin: the net income divided by revenue (Boyer and Hult, 2005;Campbell and Savelsbergh, 2005).…”

Route activity tracking and management using available technology

“…Many researchers such as Campbell and Savelsbergh (2005), Chen and Wu (2006), Nowak et al (2008), Ohlmann et al (2008), Rand (2009), Ropke and Pisinger (2006), and Tang and Wang (2008) have thoroughly studied the process. The literature on route management and delivery is diverse, but most of this research points to a small number of universal goals for route management and delivery.…”

Online Stochastic Reservation Systems

“…This creates significant opportunities at the intersection of online algorithms, combinatorial and stochastic optimization, and machine learning. In fact, increasing attention has been devoted to these issues in a variety of communities (e.g., [10,1,6,11,9,5,8]). This paper considers online stochastic reservation systems and, in particular, the stochastic multi-knapsack problems introduced in [1].…”

“…Typical applications include, for instance, reservation systems for holiday centers and advertisement placements in web browsers. These problems differ from the stochastic routing and scheduling considered in, say, [10,6,9,5] in that online decisions are not about selecting the best request to serve but rather about how best to serve a request.…”