ANALYSIS OF SHIPMENT CONSOLIDATION IN THE LOGISTICS SUPPLY CHAIN

Shipment Consolidation (SCL) is a logistics strategy that combines two or more orders or shipments so that a larger quantity can be dispatched on the same vehicle to the same market region. This dissertation aims to emphasize the importance and substantial cost saving opportunities that come with SCL in a logistics supply chain, by offering new models or by improving on the current body of literature. Our research revolves around "three main axes" in SCL: Single-Item Shipment Consolidation (SISCL), Multi-Item Shipment Consolidation (MISCL), and Pricing and Shipment Consolidation. We investigate those topics by employing various Operations Research concepts or techniques such as renewal theory, dynamic optimization, and simulation. In SISCL, we focus on analytical models, when the orders arrive randomly. First, we examine the conditions under which an SCL program enables positive savings. Then, in addition to the current SCL policies used in practice and studied in the literature, i.e. Quantity-Policy (Q-P), Time-Policy (T-P) and Hybrid Policy (H-P), we introduce a new one that we call the Controlled Dispatch Policy (CD-P). Moreover, we provide a cost-based comparison of those policies. We show that the Q-P yields the lowest cost per order amongst the others, yet with the highest randomness in dispatch times. On the other hand, we also show that, between the service-level dependent policies (i.e. the CD-P, H-P and T-P), H-P provides the lowest cost per order, while CD-P turns out to be more flexible and responsive to dispatch times, again with a lower cost than the T-P. In MISCL, we construct dispatch decision rules. We employ a myopic analysis, and show that it is optimal, when costs and the order-arrival processes are dependent on the type of items. In a dynamic setting, we apply the concept of time-varying probability to integrate the dispatching and load planning decisions. For the most common dispatch objectives such as cost per order, cost per unit time or cost per unit weight, we use simulation and observe that the variabilities in both cost and the optimal consolidation cycle are smaller for the objective of cost per unit weight. Finally on our third axis, we study the joint optimization of pricing and time-based SCL policy. We do this for a price- and time-sensitive logistics market, both for common carriage (transport by a public, for-hire trucking company) and private carriage (employing one's own fleet of trucks). The main motivation for introducing pricing in SCL decisions stems from the fact that transportation is a service, and naturally demand is affected by price. Suitable pricing decisions may influence the order-arrival rates, enabling extra savings. Those savings emanate from two sources: Scale economies (in private carriage) or discount economies (in common carriage) that come with SCL, and additional revenue generated by employing an appropriate pricing scheme. Throughout the dissertation, we offer numerical examples and as many managerial insights as possible. Suggestions for future research are offered

Available-to-promise (ATP) systems: a classification and framework for analysis

Available-to-promise (ATP) systems deal with a number of managerial decisions related to order capture activities in a company, including order acceptance/rejection, due date setting, and resource scheduling. These different but interrelated decisions have often been studied in an isolated manner, and, to the best of our knowledge, no framework has been presented to integrate them into the broader perspective of order capture. This paper attempts to provide a general framework for ATP-related decisions. By doing so, we: (1) identify the different decision problems to be addressed; (2) present the different literature-based models supporting related decisions into a coherent framework; and (3) review the main contributions in the literature for each one of these. We first describe different approaches for order capture available in the literature, depending on two parameters related to the application context of ATP systems, namely the inclusion of explicit information about due dates in the decision model, and the level of integration among decisions. According to these parameters, up to six approaches for ATP-related decisions are identified. Secondly, we show the subsequent decision problems derived from the different approaches, and describe the main issues and key references involving each one of these decision problems. Finally, a number of conclusions and future research lines are discussed.Ministerio de Ciencia e Innovación DPI2007-6134

Shipment consolidation with two demand classes: Rationing the dispatch capacity

The final publication is available at Elsevier via https://dx.doi.org/10.1016/j.ejor.2018.03.016 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/We analyze the problem faced by a logistics provider that dispatches shipment orders (parcels or larger packages) of two order classes, viz. expedited and regular. Shipment orders arrive according to a compound Poisson process for each class. Upon an arrival, the logistics provider may continue consolidating arriving orders by paying a holding cost. Alternatively, the provider may dispatch, at a fixed cost, a vehicle containing (a portion of) the load consolidated so far. In addition, the provider must specify the composition of each dispatch by allocating (rationing) the volume of the vehicle between expedited and regular shipment orders. We model this problem as a continuous-time Markov Decision Process and minimize the expected discounted total cost. We prove the existence of quantity-based optimal threshold policies under particular conditions. We also structurally analyze the thresholds of these optimal policies. Based on these structural properties, we develop an efficient solution approach for large problem instances which are difficult to solve using the conventional policy-iteration method. For two real-life applications, we show that the quantity-based threshold policies derived using the proposed approach outperform the time policies used in practice.Türkiye Bilimsel ve Teknolojik Araştirma Kurumu [1059B191400567

Revenue Management for Make-to-Order and Make-to-Stock Systems

With the success of Revenue Management (RM) techniques over the past three decades in various segments of the service industry, many manufacturing firms have started exploring innovative RM technologies to improve their profits. This dissertation studies RM for make-to-order (MTO) and make-to-stock (MTS) systems. We start with a problem faced by a MTO firm that has the ability to reject or accept the order and set prices and lead-times to influence demands. The firm is confronted with the problem to decide, which orders to accept or reject and trade-off the price, lead-time and potential for increased demand against capacity constraints, in order to maximize the total profits in a finite planning horizon with deterministic demands. We develop a mathematical model for this problem. Through numerical analysis, we present insights regarding the benefits of price customization and lead-time flexibilities in various demand scenarios. However, the demands of MTO firms are always hard to be predicted in most situations. We further study the above problem under the stochastic demands, with the objective to maximize the long-run average profit. We model the problem as a Semi-Markov Decision Problem (SMDP) and develop a reinforcement learning (RL) algorithm-Q-learning algorithm (QLA), in which a decision agent is assigned to the machine and improves the accuracy of its action-selection decisions via a “learning process. Numerical experiment shows the superior performance of the QLA. Finally, we consider a problem in a MTS production system consists of a single machine in which the demands and the processing times for N types of products are random. The problem is to decide when, what, and how much to produce so that the long-run average profit. We develop a mathematical model and propose two RL algorithms for real-time decision-making. Specifically, one is a Q-learning algorithm for Semi-Markov decision process (QLS) and another is a Q-learning algorithm with a learning-improvement heuristic (QLIH) to further improve the performance of QLS. We compare the performance of QLS and QLIH with a benchmarking Brownian policy and the first-come-first-serve policy. The numerical results show that QLIH outperforms QLS and both benchmarking policies

Essays on Shipment Consolidation Scheduling and Decision Making in the Context of Flexible Demand

This dissertation contains three essays related to shipment consolidation scheduling and decision making in the presence of flexible demand. The first essay is presented in Section 1. This essay introduces a new mathematical model for shipment consolidation scheduling for a two-echelon supply chain. The problem addresses shipment coordination and consolidation decisions that are made by a manufacturer who provides inventory replenishments to multiple downstream distribution centers. Unlike previous studies, the consolidation activities in this problem are not restricted to specific policies such as aggregation of shipments at regular times or consolidating when a predetermined quantity has accumulated. Rather, we consider the construction of a detailed shipment consolidation schedule over a planning horizon. We develop a mixed-integer quadratic optimization model to identify the shipment consolidation schedule that minimizes total cost. A genetic algorithm is developed to handle large problem instances. The other two essays explore the concept of flexible demand. In Section 2, we introduce a new variant of the vehicle routing problem (VRP): the vehicle routing problem with flexible repeat visits (VRP-FRV). This problem considers a set of customers at certain locations with certain maximum inter-visit time requirements. However, they are flexible in their visit times. The VRP-FRV has several real-world applications. One scenario is that of caretakers who provide service to elderly people at home. Each caretaker is assigned a number of elderly people to visit one or more times per day. Elderly people differ in their requirements and the minimum frequency at which they need to be visited every day. The VRP-FRV can also be imagined as a police patrol routing problem where the customers are various locations in the city that require frequent observations. Such locations could include known high-crime areas, high-profile residences, and/or safe houses. We develop a math model to minimize the total number of vehicles needed to cover the customer demands and determine the optimal customer visit schedules and vehicle routes. A heuristic method is developed to handle large problem instances. In the third study, presented in Section 3, we consider a single-item cyclic coordinated order fulfillment problem with batch supplies and flexible demands. The system in this study consists of multiple suppliers who each deliver a single item to a central node from which multiple demanders are then replenished. Importantly, demand is flexible and is a control action that the decision maker applies to optimize the system. The objective is to minimize total system cost subject to several operational constraints. The decisions include the timing and sizes of batches delivered by the suppliers to the central node and the timing and amounts by which demanders are replenished. We develop an integer programing model, provide several theoretical insights related to the model, and solve the math model for different problem sizes

Due date quotation in make-to-order systems with lead time sensitive customers

Due date management is a central issue when production is triggered by customer orders. In a wide range of industries, especially if either craftsmanship is necessary or small scale project management is employed, quoting short but still attainable due dates and sustaining the highest return for the company in the long run provides an important competitive edge. In this study, we consider a single stage make-toorder manufacturing system, where customers are quoted hundred percent reliable due dates, immediately after they arrive. Lead time sensitive customers are offered price discounts in return for due dates further out. Still, quoted lead times cannot be arbitrarily long, and strict upper bounds are imposed on these depending on the type of the customer order. The scheduler does not have any information about the future arrivals in terms of their type and timing, and s/he needs to make decisions in an online setting without prior information about the arrival process or the attributes. In this thesis, a framework which evaluates the potential decisions for each order in conjunction with the current temporary production schedule is introduced. Using this framework, a group of algorithms is developed which aim to maximize the long term profit per unit time by estimating the future implications of accepting an order with a certain due date. Computational results demonstrate that under mild congestion and relatively frequent arrival of high-margin orders, this group of algorithms outperform first-come-first-served (FCFS) order selection and sequencing approach which is typical in many contexts

Order Assignment and Resource Reservation: An Optimization Model and Policy Analysis

To maintain a competitive edge, companies today must be able to efficiently allocate resources to optimally commit and fulfill requested orders. As such, order processing and resource allocation models have become increasingly sophisticated to handle the complexity of these decisions. In our research, we introduce a model that integrates production scheduling, material allocation, delivery scheduling, as well as functions involving commitment of forecast demand for configure-to-order (CTO) and assemble-to-order (ATO) business environments. The model is formulated as a Mixed Integer Program (MIP) and seeks to maximize revenue by trading off commitment of higher profit forecast orders with the production and delivery schedule of lower profit accepted orders. Our model is particularly useful for testing different policies relating to order commitment, delivery mode selection and resource allocation

Collaborative Procurement and Due Date Management in Supply Chains

In this thesis we analyze the procurement process of buyers and supply decisions of manufacturers. Companies are looking for ways to decrease their procurement costs, which account for a large percentage of the supply chain costs. We study the effects of demand aggregation and collaborative procurement on buyers' profitability. First, we make a high-level analysis and consider a market with multiple buyers and suppliers where multi-unit transactions for multiple items take place. The procurement costs are effected by economies of scale in the suppliers' production costs and by economies of scope in transportation. We design buyer strategies that model different collaboration levels and assess the role of collaboration under varying market conditions. Next, we analyze the procurement process at a lower level and identify benefits of inter-firm collaboration among buyers who are potential competitors in the end market. We adopt a game-theoretic approach to explore the economics of the basic mechanism underlying collaborative procurement, and determine the conditions that makes it beneficial for the participants. Besides low procurement costs, important considerations in supplier selection are responsiveness and the reliability of the suppliers in meeting demand. Hence, manufacturers face the pressure for quoting short and reliable lead times. We cover several aspects of the manufacturer's problem, such as quoting reliable due-dates based on current workload in the system, maximizing profit considering the lateness cost incurred due to late deliveries, and deciding on the level of inventory to increase responsiveness. We employ a model where demand arrival and manufacturing processes are stochastic, and obtain insights on the optimal due-date quotation policy and on the optimal inventory level.Ph.D.Committee Chair: Keskinocak, Pinar; Committee Co-Chair: Griffin, Paul M.; Committee Member: Ammons, Jane C.; Committee Member: Ayhan, Hayriye; Committee Member: Chang, Yih-Lon

How to provide a humanitarian warehouse location model with data - An assessment of scenario creation and data availability at the United Nations High-Commissioner for Refugees (UNHCR)

At the end of 2014, 38 million people around the world had fled their homes due to man-made disasters such as war, armed conflict and violence. To save the lives and alleviate the suffering of these refugees and displaced is the purpose of Humanitarian Logistics. Preparedness is of key importance in humanitarian organisations as it is a tool to reduce the impact of coming events. One common preparedness measure is prepositioning, i.e. to keep stock ready in anticipation of a disaster to ensure quick dispatch after its onset. Prepositioning is one of the measures UNHCR, the United Nations Refugee Agency, is engaged in to increase its general preparedness. The volumes stored in global stockpiles allows the organisation to assist up to 600 000 refugees with emergency relief within 72 hours. To deliver to this high standard, the geographical placement of the global warehouses of UNHCR is paramount. Currently the organization has seven global stockpiles located in Cameroon, Denmark, Dubai, Ghana, Jordan, Kenya, and Tanzania. To ensure the optimality of the warehouse distribution the UNHCR has developed a humanitarian facility location model in collaboration with Lund University, BI School in Oslo and North Eastern University in Boston. This model allows the organisation to computationally determine where each stockpile should be placed and the aim is to implement the model by Q3 2017. Before that can happen existing barriers and challenges need to be identified and overcome, which is the purpose of this thesis. This was carried out by performing an in-depth case study at the regional headquarters in Budapest, Hungary, including a survey at the bi-annual Logistics Cluster meeting and a field visit to Amman, Jordan. The thesis found eight challenges associated with the implementation of the model regarding scenario creation and data availability that can be classified into four areas of improvement that are key to overcome them. The current upgrade of the ERP system provides a golden window of opportunity to mitigate these challenges. The four areas that need to be improved are increased internal communication, enhanced preparedness, staff training and increased functionality of the ERP system. Increased communication and enhanced preparedness has to do with that the contingency plans for preparedness are not shared or aggregated within the organisation and that much information is stored outside the ERP system in offline spread sheets and communicated via email. This is due to suboptimal staff behaviour in terms of data input in the systems and choice of communication channels. In addition the ERP system of UNHCR does not contain sufficient functionality to feed the model or share information throughout the organisation. Only 35% of the functional requirements of the model can currently be satisfied. Another issue of the ERP is that the information that is stored is not sufficiently detailed which greatly hampers its usability. Mode of transport is a prime example where 67% of all logs are generically classified instead of stating the used one. Further standardising the core relief items shipped could also enable automatization of delivery information such as weight and volume of shipments, something which is currently done manually. To feed the model with future scenarios the research team is recommended to create a baseline scenario by using the UNHCR Population statistics and the dollar worth of the standard aid provided. Sensitivity analysis can then be used to find the best and worst case scenario for the supply chain. When the new functionality of the ERP system and the demand application Demantra is implemented it will become possible to extract future demand scenarios directly from the systems of UNHCR. Until then this method will provide future scenarios necessary to run the model. This thesis, being one of the first to evaluate scenario creation and data availability for humanitarian facility location models, has also found a need for future research when it comes to conflict disasters and a greater need for transparency in the field of Humanitarian logistics. Most literature deals with facility location in the context of natural disasters. Little research exists to know if this is transferable to man-made disasters in a good way. Also, most articles are not sufficiently transparent in how the parameterisation of the supply chains was carried out or how the scenarios were created. However, the need for this kind of decision support tools will only become more important as more disasters occur and the current number of displaced people in the world is the highest in the history of mankind.I slutet av 2014 hade 38 miljoner människor runt om i världen flytt sina hem till följd av krig, konflikt och våld. Att rädda liv och minska lidandet för dessa flyktingar är syftet med humanitärlogistik. Beredskap en nyckelroll i humanitära organisationer eftersom det är ett verktyg för att minska det negativa genomslaget av framtida händelser. En vanlig beredskapsåtgärd är att så kallad för-positionering (engelskans prepositioning), det vill säga att ha lagervaror redo inför en katastrof för att säkra snabba leveranser efter dess utbrott. Förpositionering är en av de åtgärder UNHCR, FN:s flyktingorgan, använder för att öka sin generella beredskap. Volymerna som lagras i de globala lagren tillåter organisationen att bistå upp till 600 000 flyktingar med nödhjälp inom 72 timmar. För att kunna leverera till denna höga standard är den geografiska placeringen av de globala lagren av central betydelse. För närvarande har organisationen sju globala lager i Kamerun, Danmark, Dubai, Ghana, Jordanien, Kenya och Tanzania. För att säkerställa att denna placering är optimal har UNHCR utvecklat en humanitär lagerplaceringsmodell tillsammans med Lunds tekniska högskola, BI Handelshøyskolen i Oslo och North Eastern University i Boston. Modellen möjliggör för organisationen att matematiskt bestämma var varje lager bör placeras. Målet är att implementera modellen i organisationen till tredje kvartalet 2017. För att detta ska kunna ske måste existerande barriärer och utmaningar identifieras och övervinnas, vilket är examensarbetets syfte. Examensarbetet genomfördes genom en djupgående fallstudie på UNHCR:s regionala högkvarter i Budapest, Ungern, och inkluderade en enkätundersökning på det halvårliga Logistik-klustermötet samt ett fältbesök i Amman, Jordanien. Examensarbetet fann åtta utmaningar kopplade till implementeringen av modellen när det gäller scenarioplanering och datatillgänglighet. Dessa kan delas upp i fyra förbättringsområden som är nyckeln till att övervinna dem. Den nuvarande uppgraderingen av ERP-systemet innebär ett gyllene tillfälle att göra detta. The fyra områden som behöver förbättras är ökad intern kommunikation, förstärkt beredskap, kompetensutveckling för personalen och ökad funktionalitet i ERP-systemet. Ökad kommunikation och stärkt beredskap har sin grund i att beredskapsplanerna inte delas eller aggregeras internt i organisationen och att mycket information sparas utanför ERP-systemet i fristående kalkylark och delas via e-post. Detta beror på suboptimal handläggning av de anställda när det gäller att lägga in data i systemen och i val av kommunikationskanaler. Dessutom har UNHCR:s ERP-system inte tillräcklig funktionalitet för att mata modellen eller dela information inom organisationen. Bara 35 % av de funktionella kraven modellen har kan tillgodoses i nuläget. En annan ERP-relaterad fråga är att informationen som sparas inte är tillräckligt detaljerad, vilket försvårar dess användbarhet. Transportsätt är ett tydligt exempel där 67 % av alla loggar klassificeras generiskt istället för att specificera Ytterligare standardisering av kärnförnödenheter, såsom vikt och volym av försändelser, skulle möjliggöra automatisering av leveransinformation, något som för närvarande görs manuellt. För att mata modellen med framtida scenarier rekommenderas forskargruppen skapa ett basscenario genom att använda UNHCR:s befolkningsstatistik och penningvärdet av det standardbistånd som ges. Känslighetsanalys kan sedan användas för att utvärdera bästa- och värstascenarion. När den nya funktionaliteten i ERP-systemet och behovsapplikationen Demantra är implementerad kommer det vara möjligt att extrahera framtida behovsscenarier direkt ur UNHCR:s system. Till dess kommer denna metod att göra det möjligt att skapa framtidsscenarier nödvändiga för att köra modellen. Detta examensarbete är en av de första att utvärdera scenarioskapande och datatillgänglighet för humanitära lagerplaceringsmodeller. Det har också funnit ett behov av framtida forskning när det kommer till katastrofer orsakade av krig, konflikt och våld och ett större behov av transparens inom humanitärlogistiken som fält. Största delen av litteraturen avhandlar strategisk lagerplacering efter naturkatastrofer. Lite är skrivet om huruvida detta är överförbart till andra situationer på ett bra sätt. Vidare är de flesta artiklar inte tillräckligt transparenta i hur parameteriseringen av försörjningskedjan har gått till eller de metoder som används för att skapa scenarier. Dock kommer behovet av beslutsstöd öka i takt med att fler katastrofer inträffar och det nuvarande antalet flyktingar är den högsta i mänsklighetens historia.Utvärdering av scenarioplanering och datatillgänglighet möjliggör optimal lagerplacering hos FN:s flyktingorgan UNHCR 2016-05-10, Karolina Lindén och Peter Dahl, Lunds tekniska högskola Humanitärt bistånd kräver en genomtänkt och välplanerad försörjningskedja för att hjälpa världens mest utsatta. Genom en ny modell för optimal lagerplacering möjliggörs att hjälpen når fram snabbare och mer kostnadseffektivt. Ett examensarbete i humanitärlogistik på Lunds tekniska högskola har undersökt scenarioplanering och datatillgänglighet hos FN:s flyktingorgan UNHCR för att se hur en humanitär lagerplaceringsmodell kan förses med data. I slutet av 2014 hade 38 miljoner människor flytt sina hem på grund av krig, konflikt och våld världen över. FN:s flyktingorgan UNHCR är en av de biståndsorganisationer som hjälper dessa människor att överleva. För att snabbt kunna leverera hjälp måste förnödenheter så som tält och filtar finnas tillgängliga på strategiska platser i världen. Kravet UNHCR ställer på sig själva är att kunna bistå 600000 människor inom 72 timmar. I nuläget finns det sju stycken globala varulager, men det är oklart om deras geografiska placering är optimal för att nå kravet. För att säkerställa att placeringen är optimal har UNHCR utvecklat en humanitär lagerplaceringsmodell tillsammans med forskare från Lunds tekniska högskola, Handelshøyskolen BI i Oslo och North Eastern University i Boston. Modellen gör det möjligt för organisationen att matematiskt bestämma var varje lager bör placeras och tar hänsyn till andra faktorer än vanliga modeller gör, såsom säkerhet och politiska faktorer. För att modellen ska fungera måste den förses med data om UNHCR:s försörjningskedja och olika framtidsscenarier. Examensarbetets syfte var därför att undersöka scenarioplanering och datatillgängligheten på UNHCR för att hitta existerande utmaningar och föreslå lösningar. Arbetet genomfördes genom en djupgående fallstudie på UNHCR:s regionala högkvarter i Budapest, Ungern, och inkluderade en enkätundersökning på FN:s halvårsåterkommande Logistik-klustermöte. Det inkluderade också ett fältbesök i Amman, Jordanien. Examensarbetet fann åtta utmaningar när det gäller scenarioplanering och datatillgänglighet. Dessa kan delas upp i fyra förbättringsområden som är nyckeln till att övervinna dem. Den nuvarande uppgraderingen av ERP-systemet innebär ett gyllene tillfälle att göra detta. De fyra områden som behöver förbättras är ökad intern kommunikation, förstärkt beredskap, stärkt kompetensutveckling för personalen och ökad funktionalitet i ERP-systemet. Ökad kommunikation och stärkt beredskap har sin grund i att beredskapsplanerna som tas fram på nationell nivå inte delas eller samlas internt och att mycket information sparas utanför ERP-systemet i fristående kalkylark och delas via e-post. Detta beror på suboptimal handläggning av de anställda när det gäller att lägga in data i systemen och i val av kommunikationskanaler. Dessutom har UNHCR:s nuvarande ERP-system inte tillräcklig funktionalitet för att mata modellen eller dela information inom organisationen. Bara 35 % av de funktionella kraven modellen har kan tillgodoses i nuläget. En annan ERP-relaterad fråga är att informationen som sparas inte är tillräckligt detaljerad, vilket försvårar dess användbarhet. Transportsätt är ett tydligt exempel där 67 % av alla loggar klassificeras generiskt istället för att specificera. Ytterligare standardisering av förnödenheter, såsom vikt och volym av försändelser, skulle möjliggöra automatisering av leveransinformation, något som för närvarande görs manuellt. För att mata modellen med framtida scenarier rekommenderas forskargruppen skapa ett basscenario genom att använda UNHCR:s befolkningsstatistik och penningvärdet av det standardbistånd som ges. Känslighetsanalys kan sedan användas för att utvärdera bästa- och värstascenarion. När den nya funktionaliteten i ERP-systemet och behovsapplikationen Demantra är implementerad kommer det vara möjligt att extrahera framtida behovsscenarier direkt ur UNHCR:s system. Till dess kommer denna metod att göra det möjligt att skapa framtidsscenarier nödvändiga för att köra modellen. Detta examensarbete är en av de första att undersöka scenarioskapande och datatillgänglighet för humanitära lagerplaceringsmodeller. Det har också funnit ett behov av framtida forskning när det gäller katastrofer orsakade av krig, konflikt och våld och ett större behov av transparens inom humanitärlogistiken som fält. Största delen av litteraturen avhandlar strategisk lagerplacering efter naturkatastrofer. Lite är skrivet om huruvida detta är överförbart till andra situationer på ett bra sätt. Slutligen kommer behovet av lagerplaceringsmodeller och andra typer av beslutsstöd fortsätta öka i takt med att fler katastrofer inträffar och givet att det nuvarande antalet flyktingar är den högsta i mänsklighetens historia