Team 2056 Page 13 of 50 Special needs and business class passengers have already boarded We assume that the boarding of special needs and business class passengers is not subject to time and order optimization. Rather, airlines have an obligation to these customers for early boarding. We start our simulation clock after these special classes of passenger have already boarded. We deal only with the bulk passenger class Every passenger functions individually. We expect that effi ciency will be improved when passengers travel in groups since they are self organizing (they do not collide with each other) 3.2 Extended model ach of the following subsections detail the modeling of an extension to the basic model. The final form of our processor-based model (and, hence, the origin of our results) combines the techniques of all of these extensions (i. e, we are creating a holistic model,not modeling these features separately 3.2.1 Seat assignment The initial model assigned seats randomly and without uniqueness n the final model. this has been remedied so that there is a one- to-one correspondence between passengers and seats. The seat as- signment can be chosen in many ways. As discussed later in the paper, we investigated random, genetically evolved, back-to-front and reverse pyramid loading schemes, among others Assumptions made in Section 3.2.1 The plane is fully booked, and every seat is occupied. This tion allows us to optimize over the worst-case scenario Since airlines attempt to maximize profits, they attempt to fully book as many flights as possible. Hence, most fights will be fully or nearly fully booked. Likewise, an airline, when scheduling, will schedule assuming the fight is fully booked else risk delays). Hence, it is most important to understand the fully booked scenarioTeam 2056 Page 13 of 50 • Special needs and business class passengers have already boarded. We assume that the boarding of special needs and business class passengers is not subject to time and order optimization. Rather, airlines have an obligation to these customers for early boarding. We start our simulation clock after these special classes of passenger have already boarded. We deal only with the bulk passenger class. • Every passenger functions individually. We expect that effi- ciency will be improved when passengers travel in groups since they are self organizing (they do not collide with each other). 3.2 Extended Model Each of the following subsections detail the modeling of an extension to the basic model. The final form of our processor-based model (and, hence, the origin of our results) combines the techniques of all of these extensions (i.e., we are creating a holistic model, not modeling these features separately). 3.2.1 Seat assignment The initial model assigned seats randomly and without uniqueness. In the final model, this has been remedied so that there is a one￾to-one correspondence between passengers and seats. The seat as￾signment can be chosen in many ways. As discussed later in the paper, we investigated random, genetically evolved, back-to-front and reverse pyramid loading schemes, among others. Assumptions made in Section 3.2.1 • The plane is fully booked, and every seat is occupied. This assumption allows us to optimize over the worst-case scenario. Since airlines attempt to maximize profits, they attempt to fully book as many flights as possible. Hence, most flights will be fully or nearly fully booked. Likewise, an airline, when scheduling, will schedule assuming the flight is fully booked (or else risk delays). Hence, it is most important to understand the fully booked scenario