Concepts in Disaster Management

Concepts in cataclysm ManagementCHAPTER II literary works REVIEW2.1 Broader Views on hazard Management2.1.1 Definition of happening chance has been defined in some unalike ways. Indeed, there is no circumstantial definition for a hazard (Eshghi Larson, 2008).In complete form, Emergency Events Database (EM-DAT) defines hazards as A situation or event which e realplacewhelms local capacity, necessitating a ask to the national or international level for external assistance, or is recognize as such by a multilateral result or by at least two sources, such as national, regional or international assistance groups and the media (Centre for Research on the Epidemiology of Disasters (CRED), 2004). Be clinical depression et al. (2007) aim an accumulation of widespread losses over multiple economic sectors, associated with a innate hazard event, that overwhelms the readiness of the stirred population to cope as a definition of a adventure. world(prenominal) Federation on ros y Cross and Red Crescent (IFRC) defines a cataclysm as a sudden, calamitous event that seriously disrupts the functioning of a community or federation and ca purposes land, real(a), and economic or environmental losses that exceed the communitys or societys ability to cope victimisation its own visions (IFRC, 2008). van Wassenhove (2006) proposes a interruption that physi phoney affects a system as a whole and threatens its priorities and intentions as a definition of fortuity, trance Asian Disaster Reduction warmheartedness (ADRC, 2008) defines adventure as a serious affray of the functioning of society, create widespread gentleman, material or environmental losses which exceed the ability of touch on society to cope using only its own resources, which is resembling with Reliefwebs (2008) definition. Emergency Management Australia (EMA, 2008) defines disaster as a serious disruption to community life which threatens or causes death or injury in that community and/ or damage to property which is beyond the day-today capacity of the overconfident statutory authorities and which requires special mobilization and organization of resources separate than those usually available to those authorities, while tinge is defined as An event, certain or imminent, which endangers or threatens to endanger life, property or the environment, and which requires a momentous and coordinated chemical reaction. (EMA, 2008).2.1.2 Disaster TypesWith a wide variability of disaster definition, it is perceivable to have different initial classifications for disasters (Eshghi Larson, 2008 Shaluf 2007a, b). Canadian Disaster Database (2008) catego ascendings disasters into tailfin different typecasts as summarized in circumvent 1. hold over 1. Disaster types(Source Canadian Disaster Database, 2008)Disaster typesEncompassesBiologicalEpidemic, infestationGeologicalEarthquake, landslide, tsunami meteoric and hydrologicalCold wave, drought, flood, f be/ thunder storm, heat wave, hurri stinkpote/ typhoon, snow avalanche, storm surges, storm-freezing rain, storm-unspecified/ other, storm-winter, fracture, wildfireConflictTerrorism, civil unrest expertAccident-industrial, accident-other, accident-transport, fire, hazardous chemicalsvan Wassenhove (2006) proposes a metrics (see Table 2) to understand disasters.Table 2. Categorization of disasters base on van Wassenhove (2006)Natural unrealSudden-onsetEarthquake, hurri passele, tornadoTerrorist attack, coup detat, chemical leakSlow-onsetFamine, drought, povertyPolitical crisis, refugee crisisIn general, Shaluf (2007a, b) categorises disasters into three typesNatural disasters, which ar catastrophic events resulting from inbred causes such as volcanic eruptions, tornadoes, earthquakes, etc.Man made disasters, which atomic number 18 those catastrophic events that result from human being decisions.Hybrid disasters are those disasters that result from both human error and cancel forces.In fu rther detail, Shaluf (2007b) breaks down each type of disasters and gives examples and characteristics, as can be seen in Table 3.Table 3. Disaster types, taken from Shaluf (2007b)Disaster typeCharacteristicsSub-disasterName of disastersNaturalA natural disaster is a natural phenomenonA natural disaster is an unplanned and socially degraded event with a sudden and severe disruptive effectA natural disaster is single event over which no human has considerThe impact of natural disaster is localized to a geographic region and specific time limitThe consequences of a natural disaster are felt at the place and time of its communicaterenceThe disaster can be a high-impact disaster (e.g. a flood) that has a greater directly effect on the community over a extended period quick onset disasters imply earthquakes, flash floods, hurricanes, volcanic eruptions, landslides, tsunamis, in arrears onset disasters, droughts, floods, and epidemicsNatural phenomena beneath the earths surfaceEa rthquakesTsunamisVolcanic eruptionsTopographical phenomenaLandslidesAvalanchesMeteorological/ hydrological phenomenaWindstorms (Cyclones, typhoons, hurricanes)TornadoesHailstorms and snowstormsSea surgesFloodsDroughtsHeat waves/ could wavesBiological phenomenaInfestations (locust swarms, mealy bug)Epidemics (cholera, dengue, ebola, malaria, measles, meningitis, yellow fever, HIV/ AIDS, tuberculosis)Man-madeCharacteristics of socio-technical disastersA socio-technical disaster is a man-made eventA socio-technical disaster occurs in an organisation due to the interaction between internal factors and external factorsIt arises suddenly when the disaster occurs it does so as a shockA socio-technical disaster is a complex system of interdependenceThe impact of a socio-technical disaster sometimes transcends geographical boundaries and can even have trans-generational do (e.g. Three Mile Island, Bhopal, Chernobyl)Socio-technical disasters do not always have their mop consequences at the point of occurrence the worst effects can occur long after the eventSocio-technical disasters are characterized by a low probability/ high consequences eventSudden-impact disasters (e.g. air/road/rail accident) are usually of short duration and have a limited direct effect on the local communitySocio-technical disasters arise not because of a single factor but of accumulated unnoticed eventsDisaster involves guidance procedures which must be maintained, and counseling businesss must be coped with under the conditions of a major technical emergency involving threats of injury and loss of lifeRapid onset disasters include fires, scientific disasters, industrial accidents, and transferral accidentsAn inquiry idea is requiredSocio-technicalTechnological disastersFireExplotions (munitions explosions, chemical explosions, nuclear explosions, mine explosions) evasionToxic releasePollutions (pollution, acid rain, chemical pollution, atmospheric pollution)Structural explode of physi cal assetsTransportation disastersAir disastersLand disastersSea disastersStadia or other public places failuresFireStructural collapseCrowd stampede toil failureCom dumb bringer system breakdownDistribution of sorry returnions warNationalCivil war between armed groups in the corresponding countryCivil strikesCivil disorderBomb threats/ terrorist attackInter-national ceremonious warWar between two armies from different countriesSiegesBlockadesNon-conventional warnuclearChemicalBiologicalHybridThe characteristics of a loanblend disaster can be the characteristics of both man-made and natural disastersNatural and man-made eventsFloods provoke community built on known floodplainLocation of residential premises, factories, etc., at the foot of an active volcano, or in an avalanche subject orbital cavityLandslidesSlightly different from those, EM-DAT (2008a) classifies disasters into three groupsNatural disastersTechnological disastersComplex emergenciesRegarding its reach in te rms of sufferer number and/ or geographic areas affected, Gad-el-Hak (2008) distinguishes disasters into five categories as can be seen in Table 4.Table 4. Disaster scope in terms of number of victims and/ or geographic area affected(Source Gad-el-Hak, 2008) settingCategoryNo. of sufferersGeographic areas affectedScope ISmall disasterOrScope II medium disaster10-100 personsor1-10 km2Scope IIILarge disaster100-1,000 personsOr10-100 km2Scope IVEnormous disaster1,000-104 personsOr100-1,000 km2Scope VGargantuan disaster 104 personsOr 1,000 km2 maculation the definition of natural disasters and technological disasters are principally the kindred as those proposed by Shaluf (2007a, b), complex emergencies take away a further exploration. Alballa-Bertrand (see Alballa-Bertrand, 2000) proposes the adjacent definition for a complex humanist emergency or, in short, complex emergencyA purposeful and supposed(prenominal) neutral retort, intend mostly to counteract the worse effects of the colossal human destitution that derive from an overt political phenomenon, which takes the form of a violent, entrenched and long-lasting factionalist mesh or imposition with ultimate institutional aims.On the other hand, ReliefWeb (2008) defines a complex emergency as A multifaceted humanitarian crisis in a country, region or society where there is a total or considerable breakdown of warrant resulting from internal or external conflict and which requires a multi-sectoral, international response that goes beyond the mandate or capacity of any single agency and/or the ongoing UN country program. Such emergencies have, in particular, a scourge effect on children and women, and call for a complex chemical chain of responses. While Complex Emergency Database (CE-DAT) (2008) defines complex emergency as all crises characterized by extreme vulnerability that display the pursuit featuresThere constitute the involuntariness or incapability of the government to give effective respon se, croaking call for external assistancePolitical oppression or armed conflictDisplacementIncreased mortality.2.1.3 The Increasing Trend of Disaster OccurrencesLichterman (1999) predicts that the frequency of disasters and their effects seem to be increasing. By reviewing various(a) link published sources from 1900-2005, Eshghi and Larson (2008) establish Lichtermans prediction. A disaster leads to a severe trouble of society, including extensive human misery and physical loss or damage (Davis Lambert, 2002). Both natural and man-made disasters are likely to raise another five-fold over the succeeding(prenominal) fifty years (from the year 2005) due to environmental degradation, rapid urbanisation and the spread of HIV/AIDS in less climbed world (Thomas Kopczak, 2005). More than 250 million people in the world are affected by disasters every year (IFRC, 2008). In the sense of natural disasters which are then divided into biological, geophysical, climatological, hydrologica l, and meteorological disasters -, CRED (see Scheuren et al., 2008) reports that there were 414 natural disaster occurrences (excluding biological disasters) in year 2007 which killed 16847 persons, affected to a greater extent than 211 million others and caused over 74.9 US$ billion in economic damages. Until year 2004, over 90 percent of natural disasters occurred in developing countries (United Nations ISDR, 2004).By including biological disasters and regrouping natural disasters into three different categories, as followsHydro-meteorological disasters comprising floods and wave surges, storms, droughts and related disasters (extreme temperatures and forest/ sponge fires), and landslides avalanchesGeophysical disasters earthquakes tsunamis and volcanic eruptions capitulation into this categoryBiological disasters consisting of epidemics and insect infestationsInternational Strategy for Disaster Reduction (ISDR) (2008) set ups data which shows that there is an increasing tend ency on the occurrences of natural disasters from 1900 to 2005, as can be seen in Table 5.Table 5. Distribution of natural disasters by offset(1900-2005, by decades*)*) 2000-2005, half dozen year periodThe increasing trends of the occurrences of natural disasters between 1900-June 2008 is as sanitary document in EM-DAT (2008b).Regarding the victims, there were 3,470,162,961 people affected by natural disasters for the period of 1991-2005 with a total of 960,502 deaths. Most of the victims (98.1% of people affected and 92.1% of people killed) were fit(p) in developing countries and least-developed countries (IFRC, 2008).2.1.4 Disaster ManagementDisaster management in addition known as emergency management (Reliefweb, 2008) is defined as schoolwide approach and activities to reduce the adverse impacts of disasters (Reliefweb, 2008), while disaster trading operations could be considered as the set of activities that are performed before, during, and after a disaster which ar e aimed at preventing loss of human life, reducing its impact on the economy, and returning(a) to a normal situation (Altay Green III, 2006). Using the terminology of disaster residue operations (DRO) as substitute to disaster operations, Pujawan et al. (2009) state that DRO consists of a variety of activities such as assessing craves, acquiring commodities, finding out priorities as well as receiving, classifying, storing, tracing and tracking deliveries. Regarding its phases, disaster management could be divided into four phases (Altay Green III, 2006) disaster mitigation, disaster preparedness, disaster response, and disaster recovery.2.1.5 The Importance of Logistics in Disaster ManagementLogistics could be defined as follows (see Sheu, 2007a 655)Logistics is the process of prep, implementing, and controlling the efficient, effective go down and storage of goods, services and related information from the point of origin to the point of consumption for the purpose of conf ormist to customers requirements at the lowest total comprise.Its system operation consists of mesh topology heading, information, transportation, broth, warehousing, material handling, and packaging (see Wu Huang, 2007 429). There are several Operational Research (OR) techniques utilize in logistics context, including the use of transportation pattern to determine the mess of warehouses and the use of assignment/ allocation model to locate production facilities (Slats et al., 1995 12), to name a few.In particular, humanitarian logistics could be defined as the process of planning, implementing and controlling the efficient, cost-effective flow and storage of goods and materials, as well as related information, from point of origin to point of consumption for the purpose of suffering the end beneficiarys requirements (Thomas Mizushima, January 2005). Similarly, Thomas and Kopczak (2005) define it as the process of planning, implementing and controlling the efficient, cost- effective flow and storage of goods and materials, as well as related information, from the point of origin to the point of consumption for the purpose of alleviating the suffering of vulnerable people. Whereas Sheu (2007a) proposes a process of planning, managing and controlling the efficient flows of substitute, information, and services from the points of origin to the points of destination to meet the urgent requirements of the affected people under emergency conditions as a definition of emergency logistics.Moreover, disaster easing is usually put aside for sudden upheavals such as natural disasters (earthquakes, avalanches, hurricanes, floods, fires, volcano eruptions, etc.) and very few man-made disasters such as terrorist acts or nuclear disasters (Kovcs Spens, 2007). Relief itself could be understood as assistance and/or discourse during or after disaster to meet the life preservation and rudimentary subsistence needs. It can be of emergency or protracted duration (Re liefweb, 2008).It has been already generally well-known that logistics play a vital role in emergency management. Sheu (2007a) declares that, due to the possibility of disasters occurrences anytime around the world with huge effects, emergency logistics management had appeared as a world(a)-noticeable subject matter. People which are affected by disasters and are uprooted from their rights for food, housing, livelihood and other means of supporting themselves need the obstetrical delivery of food, medicine, tents, sanitation equipment, tools and other necessities (Whybark, 2007). The science of logistics and try chain management is becoming more vital for humanitarians (van Wassenhove, 2006), and the subject of disaster management is an suddenly fascinating one that is growing in importance (van Wassenhove, 2003 19). Oloruntoba (2005) states that, regarding the Indian naval tsunami context, the scale of damage and subsequent response lead to capers of coordination, transportat ion and dissemination among responding groups. In other affected areas of the Indian Ocean tsunami, Thomas (summer/fall 2006) reports that, at the 60-day point, regardless of the enormous relief efforts, only 60% of the families report receiving well-timed and sufficient aid. It is therefore acceptable to conclude that good logistics planning plays an important role to the success of an emergency program (Davis Lambert, 2002 109).Humanitarian logistics is intrinsic to disaster relief for some reasons (Thomas Kopczak, 2005)It is crucial to the effectiveness and speed of response for main humanitarian programs, such as health, food, shelter, water, and sanitationIt can be one of the most expensive elements of a relief effort as it includes procurement and transportationSince the logistics department handles tracking of commodities done the supply chain, it is oftentimes the repository of data that can be analyzed to offer post-event knowledge.In his paper, McEntire (1999) states that the disaster studies must discover ways to improve the provision of relief after certain catastrophe hits. This statement is in line with Perrys (2007) finding which accentuates the availability of logistician cadres as a key element of disaster response, as part of needs assessment and for procuring, transporting, and distributing the relief provisions. Regarding the relief of the Indian Ocean tsunami, the humanitarian organizations providing those relieves acknowledged that relief can and needs to be faster and more efficient (Thomas, 2005). Together with hurricane Katrina disaster, the Indian Ocean tsunami lead to the gap of the inability to connect the aid provided with the aid received (Thomas, 2005) in spite of the unprecedented giving during those two misfortunes. It is also pointed out by Tolentino Jr. (2007) that the Indian Ocean tsunami has provided the will to radically improve disaster management and planning, an issue Trims (2004 224) research agrees with, in a br oader disaster relief context. Furthermore, the development of new technology for track/trace and disaster relief supply chains is proposed as one of ways to improve the delivery of humanitarian relief (Baluch, 2007). In the context of the participation of non-governmental organizations (NGOs) in worldwide emergencies (e.g. volcanic eruptions, earthquakes, floods, war), Beamon and Kotleba (2006) point out that the capability of an NGOs supply chain and logistics operations directly influences the success of a relief effort. Whereas Pujawan et al. (2009) propose information visibility, coordination, accountability, and professionalism as successful requirements of logistics for DRO.2.2 Some Previous Works in Logistics ManagementThe following paragraphs will give a short overview on several aspects in logistics management, especially those which are perceived as having relevance with the current research. They include diffusion meshwork institution problem, location-allocation pro blem ( traffic circle), vehicle routing problem (VRP), and location-routing problem (LRP), respectively.2.2.1 Distribution Network Design ProblemCiting Chopra (2003), diffusion can be seen as the steps taken to move and store a product from the supplier stage to a customer stage in the supply chain. While diffusion networks can be defined as networks that carry the flow of some commodity or entity, using a routing rule that is intended to be effective and even optimal (Whittle, 2007), and statistical distribution network itself could be viewed as akin with the terminology producer network (Ambrosino Scutell, 2005 611).Distribution network design problem tackles the issues of optimizing the flows of commodities through an existing distribution network as well as improving the performance of the existing network by selecting the most take over setting of the facilities in the network aimed at satisfying the companys goal at one hand and minimising the boilersuit costs at the oth er hand (Ambrosino Scutell, 2005 611). It involves facility location, transportation and inventory decisions (Ambrosino Scutell, 2005 611). In other nomenclature, the aim of distribution network design problem is on deciding the best(p) way of moving goods or products from resource/ supply points to destination/ demand points which is performed by determining the structure of the network, in a such a way that the customer demands are commodious and the total distribution costs are minimized (Ambrosino et al., 2009 442). In Amiris (2006 567-568) paper, distribution network design is stated as involving the simultaneous decisions on the best settings of both plants and warehouses and on the best strategy in the sense of product distribution from the plants to the warehouses and from the warehouses to the customers, respectively.Meanwhile, the term distribution system design refers to the strategic design of the logistics infrastructure and logistics strategy to deliver products f rom one or more sources to the customers (Goetschalckx, 2008 13-1) and similar to Ambrosino et al.s (2009) statement on distribution network design problem focuses on five phases of interconnected decisions, as follows (Goetschalckx, 2008 13-2)Establishing the appropriate quantity of distribution centers (DCs) orbit up the location of each DCAllocating customers to each DCAllocating appropriate commodities to each DC andDetermining the throughput and storage capacity of each DC. assorted models and approaches that have been built for designing distribution system or distribution network, to name a few, are (Goetschalckx, 2008 13-8-13-15 Lapierre et al., 2004) K-median model, location-allocation model, warehouse location model, Geoffrion and Graves distribution system design model, models that focus on mathematical description of cost functions on each route in order to incorporate returns to scale, models of which intentness are in shipments on hub-to-hub routes regarding discoun ts, and models that aim at solving the warhead transportation problem precisely.2.2.2 Location-Allocation Problem (LAP)As previously stated in Goetschalckx (2008), LAP could be seen as part of distribution network design problems. Given the place of a set of customers with different demands, LAP is refer with the selection of supply centres positions dedicated for serving the customers as well as the decision of the allocation of the customers to supply centres, with both of them are aimed at optimizing a given criterion (Hsieh Tien, 2004 1017). It is also assumed that there is no interaction among supply centres. The criterion could be single such as transportation costs (see, for example, Goetschalckx, 2008 Zhou Liu, 2003 Manzini Gebennini, 2008) or it may comprises several aspects (see, for example, Mitropoulos et al., 2006).The following paragraphs provide some previous researches on LAP.The un-capacitated-type LAP with rectilinear distances could be found in Hsieh and Tien (2004). In this paper, the authors propose a heuristic method which is based on Kohonen self-organising feature maps (SOFMs).Sometimes distribution networks are built in hierarchies, where high-level distribution channels are constructed in straight lines from which low-level channels stem. Furthermore, destinations are allocated to branching facilities in high-level channels through low-level channels. Due to cost considerations, the number and locations of branching facilities as well as the allocation of the destinations to the aforementioned branching facilities need to be refractory correctly. Eben-Chaime et al.s (2002) paper addresses this type of problem by formulating appropriate mathematical optimisation models and subsequently proposing heuristic solution methods.Capacitated LAP with stochastic demands is intercommunicate by Zhou and Liu (2003). More specifically, they propose three types of stochastic programming models (1) pass judgment value model (EVM), (2) chanc e-constrained programming (CCP), and (3) dependent-chance programming (DCP). To solve these models efficiently, the authors develop a hybrid intelligent algorithm within which three type stochastic simulations are used. The proposed algorithm integrates the network simplex algorithm, stochastic simulation and inheritable algorithm.In more recent paper, Zhou and Liu (2007) address the LAP with brumous demands by developing three types of fuzzy programming models fuzzy expect cost minimisation model, fuzzy -cost minimisation model, and credibility maximisation model with respect to different decision criterion. To solve these models, the authors apply a hybrid intelligent algorithm developed previously (see Zhou and Liu, 2003). Nonetheless, instead of using stochastic simulations, they are developing and employing fuzzy simulations.Similar with the abovementioned paper, Wen and Imamura (2008) also address LAP with fuzzy demands. For this type of problem, they build a fuzzy -cost m odel under the Hurwicz criterion. The problem is subsequently solved using the same algorithm as in Zhou and Liu (2007).The establishment of mixed integer programming optimisation models for multi-period, multi-stage LAPs could be found in Manzini and Gebennini (2008). In their paper, the authors develop optimisation models each for the following classes of multi-period, multi-stage LAPs (1) single-commodity, multi-period, two-stage LAPs, (2) multi-commodity, multi-period, two-stage LAPs, (3) single-commodity, multi-period, two-stage open/ closed LAPs, and single-commodity, multi-period, three-stage LAPs.The application of various search methods to a generalised class of LAPs known as multi-facility location problem with generalised objects (MFLPO) is presented by Bischoff and Dchert (2009). The end of the paper gives similitude of the involved search methods for various sizes of test problem.Research on LAP in health service context could be found in Harper et al. (2005) and Mitr opoulos et al. (2006). The former addresses the need to plan health services which takes geographical aspects into consideration. The problem is formulated as a stochastic LAP. The latter paper, on the other hand, develops a bi-objective model to solve the LAP arise in determining the location of hospitals and health centres and the allocation of the patients to those facilities.2.2.3 Vehicle Routing Problem (VRP)In its most basic form (e.g. Bulbul et al., 2008 Laporte, 2007), VRP is concerned with the optimal delivery or collection routes for a limited number of identical vehicles with limited capacities from a central destination/ warehouse to a set of geographically bewildered customers. It assumes that the vehicles are at the central depot/ warehouse initially. It also requires the universe of discourse of the routes that connect the central depot/ warehouse to customers and customers to customers as well. In this type of VRP, a route must start and finish at the depot and a customer is visited by exactly one vehicle. The total demand of customers served by one vehicle could not exceed the vehicles capacity, and the ultimate goal is to minimise the total routing costs.Since its introduction by Dantzig and Ramser in 1959 (Bulbul et al., 2008), it has given rise to a rich body of works (Laporte, 2007). In 2008, searching the words vehicle routing problem by using Google scholar search results more than 21,700 entries (Golden et al. (eds), 2008).Laportes (1992) paper provides various exact methods and heuristics developed to solve the VRP. Several meta-heuristics intended to solve the classical VRP could be traced from his more recent paper (2007), while Toth and Vigos (2002) paper presents various existing exact algorithms for the solution of classical VRP. The proportion of descent heuristics, simulated annealing, and tabu search in solving VRP is addressed by Van Breedam (2001). Jozefowiez et al. (2008), on the other hand, give a mint on works that ha ve been carried out on multi-objective VRP.A range of VRP variants can be seen in Crainic and Laporte (eds., 1998), Bulbul et al. (2008), and Golden et al. (eds., 2008). Other variants also exist VRP with stochastic demands and VRP with backhaul. Different classification of VRP could be found in Pisinger and Ropkes (2007) paper. The following sub-sections mention examples of works on some of them, while new directions in modelling and algorithms for various types of LRP could be found in Part II of Golden et al.s (eds., 2008) edited book.2.2.3.1 VRP with Time WindowsIn this type of VRP, customer i may only be visited within a time windowpane ai, bi (see, e.g., Kontoravdis Bard, 1995 Badeau et al., 1997 Bouthillier Crainic, 2005 Fgenschuh, 2006 Hsu et al., 2007 Kim, et al., 2006 Dondo Cerd, 2007 Kallehauge et al., 2007).2.2.3.2 VRP with Pickup and DeliveryWhen the vehicles need to deliver commodities to customers and collect items for example, defective products from them as wel l, then this is called a VRP with pickup and deliveries. Research papers by Nagy Salhi (2005), Wassan et al. (2008), Wassan et al. (2008), Gribkovskaia et al. (2008), Hoff et al. (2009), and Ai Kachitvichyanukul (2009) are several examples on it.2.2.3.3 VRP with BackhaulIn this type of VRP, the customers are separated into two mutually exclusive subsets so that the starting line subset of customers receives commodities whereas the secant one sends back the products. Additionally, the second subset of customers are only served after the first one. The first subset is called line-haul customers and the second one is named backhaul customers. The f