A Review of Relief Supply Chain Optimization

Abstract

With a steep increase of the global disaster relief efforts around the world, the relief supply chain and humanitarian logistics play an important role to address this issue. A broad overview of operations research ranges from a principle or conceptual framework to analytical methodology and case study applied in this field. In this paper, we provide an overview of this challenging research area with emphasis on the corresponding optimization problems. The scope of this study begins with classification by the stage of the disaster lifecycle system. The characteristics of each optimization problem for the disaster supply chain are considered in detail as well as the logistics features. We found that the papers related to disaster relief can be grouped in three aspects in terms of logistics attributes: facility location, distribution model, and inventory model. Furthermore, the literature also analyzes objectives and solution algorithms proposed in each optimization model in order to discover insights, research gaps and findings. Finally, we offer future research directions based on our findings from the investigation of literature review.

A light‐touch routing optimization tool (RoOT) for vaccine and medical supply distribution in Mozambique

“…However, some differences between a private sector supply chain and a humanitarian relief chain should be noted. In the private sector, the network configuration is more stable with respect to supply and demand (quantities and entities involved), while they are challenging to predict and are less consistent in humanitarian logistics (Manopiniwes and Irohara, 2014). In addition, cost is often the sole objective in the private sector, whereas a humanitarian relief chain may prioritize rapid distribution using available resources (Tomasini and Van Wassenhove, 2009).…”

Real-time relief distribution in the aftermath of disasters – A rolling horizon approach

“…In particular, various operations research models and algorithms have been adopted to tackle emergency logistics problems (see the review articles of Altay and Green, 2006;Caunhye et al, 2012;Galindo and Batta, 2013;Manopiniwes and Irohara, 2014;Simpson and Hancock, 2009). Most previous works address the static planning problems of relief distribution, which assume that relevant input data (e.g., relief demands and delivery times) or their distributional estimates for the entire planning horizon are readily available prior to the beginning of the distribution process (i.e., the assumption of complete information).…”

“…Very few existing studies addressed the issues of evolving and uncertain information in relief distribution problems (e.g., Manopiniwes and Irohara, 2014). For instance, Wohlgemuth et al (2012) applied the dynamic vehicle routing problem with pickups and deliveries to the last mile relief distribution context.…”

“…Thus, compared to financial objectives or budget constraints, response time or completion time may be more important for emergency logistics in the aftermath of disasters. In addition, the recent review of Manopiniwes and Irohara (2014) highlighted that different objectives and mechanisms drive disaster relief supply chains. It also indicated a significant number of studies for disaster operations management that aimed to minimize the total response or completion time in order to rescue and aid as many affected people as possible as quickly as possible.…”

A two-stage priority-based MOGA for materials allocation and loading problem in large-scale emergencies

“…In recent years, emergency logistics theory has been put forward and obtained plenteous achievements (Ou et al, 2004;Manopiniwes and Irohara, 2014). The major research content of accident rescue is how to timely master and comprehensively utilize the environment information to make decision on how to distribute various relief materials from multiple material storage and collection points to handout and sub-handout points in affected areas in an efficient and reliable way.…”