Capacity allocation to sales agents in a decentralized logistics network

Many logistics systems operate in a decentralized way, while most optimization models assume a centralized planner. One example of a decentralized system is in some sea cargo companies: sales agents, who share ship capacity on a network, independently accept cargo from their location and contribute to the revenue of the system. The central headquarters does not directly control the agents' decisions but can influence them through system design and incentives. In this paper, we model the firm's problem to determine the best capacity allocation to the agents such that system revenue is maximized. In the special case of a single‐route, we formulate the problem as a mixed integer program incorporating the optimal agent behavior. For the NP‐hard multiple‐route case, we propose several heuristics for the problem. Computational experiments show that the decentralized system generally performs worse when network capacity is tight and that the heuristics perform reasonably well. We show that the decentralized system may perform arbitrarily worse than the centralized system when the number of locations goes to infinity, although the choice of sales incentive impacts the performance. We develop an upper bound for the decentralized system, where the bound gives insight on the performance of the heuristics in large systems. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

A FOCUS ON SMALL ARMS

For much of the past two years, the African Union Mission in Sudan (AMIS) has managed to achieve a semblance of stability in much of Darfur, which has been reflected in the improvement of humanitarian conditions. At the same time, the mission has come under serious international pressure to respond appropriately to the deteriorating security situation on the ground by enhancing its presence and effectiveness. Subsequently, following the decisions of the AU Peace and Security Council (PSC), AMIS has undertaken two successive enhancements. Although the last enhancement exercise was remarkably successful, it could not be considered complete without the provision of the outstanding personnel and logistics by both member countries and the international partners. Meanwhile, serious challenges continue to undermine the mission's effectiveness and its prospects, not the least of these obstacles being adequate funding. At present, the mission is in a dilemma with respect to its mandate, engaging with the parties, partners, implementation of the N'sDjamena Humanitarian Ceasefire Agreement (HCFA), and the way forward, as the AU is now almost totally dependent on external donations to sustain its Darfur operations. This article therefore explores the way forward in all these thematic areas in order to make appropriate recommendations.     

Optimal timing of switches between product sales for sports and entertainment tickets

Like airlines and hotels, sports teams and entertainment venues can benefit from revenue management efforts for their ticket sales. Teams and entertainment venues usually offer bundles of tickets early in their selling horizon and put single‐event tickets on sale at a later date; these organizations must determine the best time to offer individual tickets because both types of ticket sales consume the same fixed inventory. We model the optimal a priori timing decision for a seller with a fixed number of identical tickets to switch from selling the tickets as fixed bundles to individual tickets to maximize the revenue realized before the start of the performance season. We assume that bundle and single‐ticket customers each arrive according to independent, nonhomogeneous Markovian death processes with a linear death rate that can vary over time and that the benefit from selling a ticket in a package is higher than from selling the ticket individually. We characterize the circumstances in which it is optimal for the seller to practice mixed bundling and when the seller should only sell bundles or individual tickets, and we establish comparative statics for the optimal timing decision for the special case of constant customer arrival rates. We extend our analytical results to find the optimal time for offering two groups of tickets with high and low demand. Finally, we apply the timing model to a data set obtained from the sports industry. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

The effects of customer rebates and retailer incentives on a manufacturer's profits and sales

In some industries such as automotive, production costs are largely fixed and therefore maximizing revenue is the main objective. Manufacturers use promotions directed to the end customers and/or retailers in their distribution channels to increase sales and market share. We study a game theoretical model to examine the impact of “retailer incentive” and “customer rebate” promotions on the manufacturer's pricing and the retailer's ordering/sales decisions. The main tradeoff is that customer rebates are given to every customer, while the use of retailer incentives is controlled by the retailer. We consider several models with different demand characteristics and information asymmetry between the manufacturer and a price discriminating retailer, and we determine which promotion would benefit the manufacturer under which market conditions. When demand is deterministic, we find that retailer incentives increase the manufacturer's profits (and sales) while customer rebates do not unless they lead to market expansion. When the uncertainty in demand (“market potential”) is high, a customer rebate can be more profitable than the retailer incentive for the manufacturer. With numerical examples, we provide additional insights on the profit gains by the right choice of promotion.© 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2010