INTEGRATION MODEL FOR SCHEDULING OF PASSENGER AND CARGO AIRCRAFT FLIGHT.

Nowadays flight scheduling is very important for profitability, but it has a complex problem when compiled traditionally. This study develops an integrated model for scheduling passenger and cargo scheduling simultaneously aiming to maximize profits. Network flow techniques are used to build the model, includes a low flow, the flow of passengers and goods flow. The model is formulated using integer commodity network flow with the characteristics of NP-Hard. Because of the problems predicted a very large, this model is more difficult to solve than the problem of scheduling traditional airlines or cargo. This model is able to directly manage the relationship between passengers and cargo and is expected to be a useful planning tool to determine the appropriate fleet and schedule in the short-term operations

In the 1950s, the airline uses operations research models in solving their complex planning when planning a flight itinerary. Continuous pressure to increase profitability generating more accurate models and better solutions (Klabjan Diego, 2003).
Officers planners determine the passenger and combi into scheduling to be projected to passenger demand, market share, and flight slots at various airports (Ching Hui Tang, 2007). Eligibility check then done, especially the availability of the fleet on route flights, aircraft size, calculation of costs and revenues and fleet crew and aircraft maintenance arrangements. After the flight schedule passenger and combi made, scheduling and cargo flights were made in the plan affected the flight schedule passenger and combi, better still if the projected demand for freight and other constraints related. Improvements can act as feedback to further revise combi flights. This iteration process manually until the desired schedule obtained.

ISSN: 2320-5407
Int. J. Adv. Res. 6(1), 977-982 978 and is expected to be a useful planning tool to determine the appropriate fleet and schedule in the short-term operations.
Network flow techniques are used to build the model, includes a low flow, the flow of passengers and goods flow. The model is formulated as a problem IMCN using non characteristic polynomial hard (NP-Hard). Because the problem is expected to be very large, this model is more difficult to solve than the problem of scheduling traditional airlines or cargo.
Here only consider to be served by the low-combi combi aircraft. Although passenger aircraft can transport cargo below the main deck, the inventory space for cargo typically rely on heavy passenger baggage. If the baggage is included in scheduling, capacity of passenger baggage must be the decision variables in the model. In addition, the combi aircraft sometimes allows the seat to be added or removed, implying that the passenger capacity of the cargo may be variable, even though the average capacity of passengers or cargo can be used in the model. That is, the capacity of passengers or cargo on combi aircraft will also be the decision variables in the model. Yan and Tseng (2004), using the linear integral coupled with network flow multikomoditi. Scheduling of passengers and goods is done separately and not connected in modeling. To resolve the problem always use heuristic methods such as simplex method, engineering branch and bound, cutting plane method, Lagrangian relaxtation, engineering rows of columns and other heuristic methods.

Literature Review:-
Previous studies about the scheduling of the fleet and scheduling of flights to transport passengers have been carried out by many researchers, such as scheduling model and the routing of the fleet for the transport system (Levin, 1971), a model of scheduling and routing for the flight system (Simpson, 1969), the implementation of the program integer linear assignment problem fleet (Abara, 1989), scheduling and routing airline in the system hub and spokes (Dobson and Lederer, 1993), the assignment problem fleet: troubleshoot integer large scale (Hane etal,1995), maintenance and consideration crew in the fleet assignment (Clark et al, 1996), Yan and Young (1996), Desaulniers etal.(1997), Yan and Tseng (2002), Barnhart etal.(2002), and Lohatepanont and Barnhart (2004). As well as research in freight related has been devoted to matters such as the characteristics of the carrier air express (Chestler, 1985), network planning for an international operator of air cargo (Current et al 1986;Hall, 1989 table origin (known as OD table). Such a network is designed to be symmetrical in accordance with the current network fleet of passenger and combi fleet flows, so as to facilitate troubleshooting. There are three types of arcs, namely: 1. Passenger delivery arc, 2. Passenger holding arc, 3. Passenger demand arc.
The cargo-flow time-space networks:-Networks cargo flow periods shown in the figure shows the movement of cargo in accordance with the given time and location. According to the time sensitivity of cargo is divided into three kinds of time, one day, four days and seven days (one week). Therefore, unlike the time flow of passengers, cargo flows time flow networks represent a couple of time a specific OD. There are three types of arcs, namely: 1. cargo delivery arc, 2. cargo holding arc, 3. cargo demand arc.

980
In addition to the three main elements, there are several operating constraints that must be considered, including in particular the number of airplanes in each fleet, the quota for each airport and aircraft capacity. In addition the same flight leg in the current fleet of passenger and combi fleet network flow can be served at most one. Similarly, the same flight leg in the current cargo fleet and network flow combi fleet can be served at most one. Flights combi usually added to passenger flights, to set quotas for each airport.
Given the current network fleet, the flow of passengers and cargo as well as the current operational constraints, then the model can be formulated as a mixed integer problem. The purpose of this model is to simultaneously stream of aircraft, passengers and cargo in all the network with minimum cost. Because revenue from passenger traffic and cargo flows including the network in the form of a negative charge, this goal is equivalent to maximize profits. The model is formulated as follows: The objective function:- The model is formulated as a mixed integer multiple commodity network flow problem, where the objective is to minimize the function of the system cost, which is equivalent to maximizing profits. In particular, the first term in the objective function is the total cost of the flight, the second term is the total cost of the passenger, the third term is the total cost of freight and the fourth term is the total cost of unloading cargo. There are several obstacles that must be met. Formulations and details of constraints in the developed model is presented as follows.
Flow conservation constraint:- (2), (3) and (4)  Constraints (6) and (7) shows that the same flight leg, diarus fleet of passenger and combi fleet current network as well as network flow combi fleet and current cargo fleet, each at most once. Airport pair flight quota constraint: (8) and (9) respectively ensure that the number of all flights in each pair of airports does not exceed the quota of low and low-approved quota. Airpor flight quota constraint: (10) and (11) respectively ensure that the number of all flights at each station does not exceed the quota of low and low-approved quota. Aircraft capacity constraints: (12) and (13) respectively keep the level of passenger and cargo shipping in the carrying capacity of the aircraft.
Constraints and limits the arc current flow integralitas aircraft: 982 constraint (14), (15) and (16) hold all the current arc is in the upper and lower limits.

Conclusions:-
In this study has developed a model of integration for scheduling of air passengers at cargo flights which aims to minimize operational costs. This model is formulated as a commodity flow problems some integers which belong to the class of NP-Hard. The model is expected to be a useful planning tool for air carriers in deciding the plan scheduling of air passengers at cargo flights, in order to reduce operational costs.