Crew Costs Research Articles

A novel column generation strategy for large scale airline crew pairing problems

A crew pairing is a sequence of flight legs beginning and ending at the same crew domicile. Crew pairing planning is the primary cost-determining phase in airline crew scheduling. Optimizing crew pairings of an airline timetable is an extremely important process which helps to minimize operational crew costs and to maximize crew utilization.There are various restrictions imposed by regulations or company policies that must be considered and satisfied in crew pairing generation process. Keeping these restrictions and regulations in mind, the main goal of the optimization is the generation of low cost sets of valid crew pairings which cover all flights in airline's timetable.For this research study, already existing works related to crew pairing optimization are examined and a new column generation strategy, a pricing network design and a pairing elimination heuristic are developed as a contribution to the previous studies. In the proposed strategy, the main problem is modeled and solved as a set-covering problem and the pricing sub problem is modeled as a shortest-path problem which is efficiently solved over a duty-flight overnight connection graph by the combined usage of heuristic and exact algorithms. The proposed strategy has been tested with real world data obtained from Turkish Airlines and it is seen that it is capable of generating very competitive solutions compared to current practices in Turkish Airlines. It is also observed that there are various advantages of proposed solution approach such as sensitivity to penalty coefficients, generating less deadheads, very close solution times with a single threaded software and light weight hardware.

Trends in onshore seismic data acquisition: a case study on cable-free nodal systems

The desire to conduct onshore seismic surveys without cables has been an elusive dream since the dawn of seismic exploration. Since the late 1970s, seismic surveys were conducted with cabled multi-channels acquisition systems. As the number of channels steadily grew, a fundamental restriction appeared with hundreds of kilometres of line cables dragged on the ground. Seismic surveys within rugged terrain—across rivers, steep cliffs, urban areas, and culturally and environmentally sensitive zones—were both challenging and expansive exercises. Modern technology has made different cable-free solutions practical. High-resolution analogue to digital converters are now affordable, as are GPS radios for timing and location. Microprocessors and memory are readily available for autonomous recording systems, along with a battery the size and weight of a field nodal now promising to power an acquisition unit for as long as required for normal seismic crew operations. Many successful 2D and 3D seismic data acquisition using cable-free autonomous nodal systems were attempted in the past few years; however, there remain a number of concerns with these systems. The first concern queries whether the units are working according to manufacturer specifications during the data acquisition window. The second is the limited or no real-time data quality control that inspires sceptics to use the term blind acquisition to nodal operations. The third is the traditional question of geophone array versus point receiver acquisition. Although a string of the geophone can be connected to autonomous nodes, the preference is to deploy a single or internal geophone with the nodes to maintain the proposed flexibility of cable-free recording systems. This case study elaborates on the benefits of the cable-free seismic surveys, with specific examples of 2D and 3D exploration programs conducted in Australia in the past few years. Optimisation of field crew size, field crew resources, cost implications, and footprint to the environment, wildlife and domestic livestock will be discussed. In addition, the study focuses on the data quality/data assurance and the processes implanted during data acquisition to maintain equivalent industry standards to cable recording. Emphases will also include data analysis and test results of the geophone array versus the cable-free point receiver recording.

Construction Performance Control in Steel Structures Projects

Steel structural projects are relatively special field of construction projects. The steel structure projects differ from conventional structural engineering projects mainly in the special problems that have to be considered during construction, transportation, installation and operation. The productivity improvements are attributed to the technology advances in equipment and construction methods over the last two decades. Steel structural projects are a relatively special field of construction projects. There are many factors that impact on productivity in this field. The construction industry especially the construction of steel structure projects is rated as one of the key industries. It helps in developing and achieving the goal of society. Study and knowledge of construction productivity are very important because they influence the economics of the construction industry; this is because prior knowledge of crew productivity during construction can save money and time. Investments for these projects are very high and because of the complexity in construction of steel structure projects, various factors can highly affect overall productivity, thus the project can end up adding even more time and money in order to be completed. The main purpose of this paper is present a methodology for modeling on Mat lab to construction performance control for construction process of steel structure based on the several factors that affect the steel structure processes. The Mat lab model is used for controlling on construction productivity of steel structure projects. The construction industry may use the findings of this paper as a basis for controlling and improving productivity and construction performance for the construction of steel structure projects. The ability of the estimating team to accurately determine productivity for different activities will have a significant impact on crew cost component, time schedule of the project and improve projects’ performance. The use of the Mat lab model is expected to result in savings in cost and time schedule of construction of steel structure projects as well as savings in the cost of the overall project.

Airline Crew Augmentation: Decades of Improvements from Sabre

The objectives of the airline crew-planning process are to allocate crews to flights and create work schedules for crew members. Most airlines solve their crew-planning problem in two steps. The first step, crew pairing, is to generate optimized, anonymous pairings that cover given flight schedules. In the second step, the resulting pairings are assigned to crew members. The general pairing problem is complex because flights may require an augmented crew for safety reasons. A flight’s crew-augmentation requirement varies, depending on the characteristics of the pairings that cover it. Furthermore, airlines often impose rules to govern the coverage of a flight by different pairings. Common approaches to the problem either fix the crew-augmentation requirement a priori, or add restrictions on how the augmentation requirement is satisfied. Crew augmentation is often overlooked from an optimization perspective because of the complexities involved. The Sabre® long-haul pairing optimizer explicitly models many types of crew-augmentation processes and simultaneously considers the relevant ranks of all members within the cockpit crew. It uses state-of-the-art large-scale optimization techniques, such as branch and price, to solve the problem. In this article, we introduce the long-haul pairing optimizer that Sabre developed in the mid-1990s, and share the evolution of the models and solution algorithms for the general crew-pairing problem with augmentation. We also compare our approach with four conventional approaches to show that we can effectively solve the general crew-augmentation problem and provide significant crew cost savings to airlines.

Maritime policy and the seafaring labor market

The reports highlighting the foreseen lack of merchant marine officers for the expanding world’s fleet calls for a review in evaluating the impact of maritime policy in the seafaring labor market. This paper aims to clarify the particular characteristics of the seafaring labor market and how it can be shaped by specific maritime labor policies. The seafaring labor market in the Philippines, Poland, Germany, and Brazil as well as the general maritime labor policies in these countries is discussed. The focus on these countries leads to a comparative observation of maritime labor as a factor of production in an exporting market, in an importing market, and in a closed market, respectively, as shaped by various relevant maritime policies. Since a global policy that can regulate the maritime labor market does not exist, the trend on maritime labor supply is dynamic on a per country basis wherein crew costs, restrictions on the nationality of employed seafarers, and quality of maritime education and training play significant roles. The paper illustrates how certain aspects of a national maritime policy for the seafaring labor market affects the local market of seafarers. This, in turn, provides hints with regard to certain characteristics of a maritime labor policy of a country that can potentially be self-sufficient in meeting the demand for local seafarers or that can potentially be a future source of seafarers for the world’s merchant fleet. The exploratory investigation in this paper provides starting hypotheses that can be considered in research on maritime labor market for seafarers.

Developing a Model for Solving the Flight Perturbation Problem

Purpose : In the aviation and airline industry, crew costs are the second largest direct operating cost next to the fuel costs. But unlike the fuel costs, a considerable portion of the crew costs can be saved through optimized utilization of the internal resources of an airline company. Therefore, solving the flight perturbation scheduling problem, in order to provide an optimized schedule in a comprehensive manner that covered all problem dimensions simultaneously, is very important. In this paper, we defined an integrated recovery model as that which is able to recover aircraft and crew dimensions simultaneously in order to produce more economical solutions and create fewer incompatibilities between the decisions. Design/methodology/approach : Current research is performed based on the development of one of the flight rescheduling models with disruption management approach wherein two solution strategies for flight perturbation problem are presented: Dantzig-Wolfe decomposition and Lagrangian heuristic. Findings : According to the results of this research, Lagrangian heuristic approach for the DW-MP solved the problem optimally in all known cases. Also, this strategy based on the Dantig-Wolfe decomposition manage to produce a solution within an acceptable time (Under 1 Sec). Originality/value : This model will support the decisions of the flight controllers in the operation centers for the airlines. When the flight network faces a problem the flight controllers achieve a set of ranked answers using this model thus, applying crew’s conditions in the proposed model caused this model to be closer to actual conditions.

Low-cost long-haul carriers: A hypothetical analysis of a ‘Kangaroo route’

Given the success of short-haul, low-cost airlines in most regional markets, it was expected that low-cost airlines would next venture into long-haul markets; however, most attempts in the past decade have, like their predecessors, failed. The purpose of this paper is to demonstrate that a long-haul, low-cost operation based on a hypothetical airline that operates between Melbourne (Australia) and London (UK) can achieve a cost advantage compared to full-service airlines, but this advantage is not as great as the difference between low-cost carriers that operate in short-haul markets compared to full-service airlines (FSAs). Research to date on concept of low-cost long-haul airline operations is limited, but it does acknowledge that the cost differential between low-cost airlines and full-service airlines in short-haul regional markets is not as strong in long-haul operations. Factors such as larger and more expensive aircraft; flight-operating conditions including fuel burn; congestion around busy airports; crew costs; airport charges at main airports; and marketing issues such as branding, advertising and distribution all combine as deterrents for low-cost carriers to enter long-haul markets. This research confirms that it is possible for a low-cost, long-haul operation between Australia and the UK to attain a 13–17% cost advantage measured in cents per available seat kilometre (ASK) relative to full-service airlines.

Evaluation of Intermediate Stop Operations in Long-haul Flights

Recent crises - both economic and geopolitical - and the rise of new competitors in the form of low-cost carriers and Middle East carriers have put a heavy strain on the profitability of traditional legacy airlines worldwide. Many airlines are struggling to survive and are looking for ways to cut their operational costs.Continuously increasing fuel prices further contribute to the financial difficulties, and although airlines (and aircraft manufacturers alike) have put a significant effort on reducing the operational fuel consumption, fuel still accounts for approximately 35% of airlines’ operating expenses. Therefore many airlines seek new ways to further reduce the operational costs through improved fuel efficiency.One of the less self-evident methods to potentially significantly reduce the total operational fuel consumption is the introduction of intermediate refueling stops. Previous studies have already shown that operating existing aircraft on a long-haul flight with one or two intermediate stops can lead to potential fuel savings varying from 5% to 25% by reducing the additional fuel burn on long-haul flights referred to as transport loss. On the other hand, the concept of intermediate stop operations will also affect the operational costs through higher landing fees, an increased required maintenance effort, a longer total flight time and different crew costs. As previous studies have not addressed the additional costs or benefits of intermediate stop operations, this study aims to identify the total potential of the concept.For this purpose, a software tool was developed to analyze individual long-haul origin-destination pairs to identify the optimal operation: either direct or including an intermediate stop. Within the tool crew cost, maintenance cost and local fuel prices are determined for simulated flights according to typical operating procedures. A Dijkstra's algorithm then selects the most suitable and cost-efficient airport from a large database if an intermediate stop proves a viable option for the city-pair.A number of case studies has shown that although in all cases intermediate stops proved beneficial to reduce the total fuel burn, reducing the total operating cost depended highly on city-pair specific conditions, mainly the local fuel prices, changed crew-composition and wind direction. Still, the case studies do indicate that the concept of intermediate stop operations may offer significant cost reductions for many typical long-haul flights across the world, and could prove a viable concept to gain a competitive advantage for specific airlines and routes.

The robust crew pairing problem: model and solution methodology

We present a new robust formulation for the crew pairing problem where flight and connection times are random and vary within an interval. The model protects against infeasibility with a specified level of uncertainty and minimizes crew cost in the worst case. The resulting robust terms in the objective function and in the resource constraints are nonlinear. We apply Lagrangian relaxation to separate the nonlinear terms in the subproblem leading to a new robust formulation of the shortest path problem with resource constraints. We show that the nonlinear subproblem can be solved as a series of linear auxiliary problems. The proposed solution methodology was successful to solve industry instances in very competitive times and led to more robust crew pairing solutions as shown by simulation experiments.

A hybrid particle swarm optimization and an improved heuristic algorithm for an airline crew rostering problem

The airline crew scheduling problem is a combinatorial optimization problem and belongs to the class of NP- hard problems. An effective method for solving the airline crew scheduling problem can reduce the crew costs and improve crew satisfaction. Because of its complexity, the problem is divided into two subproblems: the crew pairing problem and the crew rostering problem. In this paper, the crew rostering problem is focused on and the objective is to generate a fairness timetable in which the workloads are distributed among each crew equally. We propose a hybrid particle swarm optimization (PSO) and an improvement heuristic (IH) to solve this problem. The IH is designed to improve the standard deviation of the workloads by picking a workload from the high workload crew and assigning it to the low workload crew. The IH improves the solution of the particle after the particle changes position each generation. The proposed algorithm is tested on actual pairing data from Thai Airways and is compared with PSO without IH and the multi-commodity network flow approach. With the combination of PSO and IH, the algorithm can improve the quality of the solution by more than 20% in most cases, and PSO with IH also outperforms the network approach in 6 out of 9 cases and especially in the large size cases for which the network approach cannot find a feasible solution.

Hybrid Simulate Annealing Algorithm Based Dynamic Crew Scheduling Research

Dynamic crew scheduling optimize the crew plan and save the human resource cost in emergency situation. On the basis of considering crew plan regulations and crew cost, the research construct dynamic crew scheduling model, using heuristic pretreatment method to generate dynamic crew routing for reducing the solution space. It form hybrid simulated annealing algorithm to solve the dynamic crew scheduling problem. The experimental result confirm the method could effectively reduce algorithm search space and calculation time and improve the operation efficiency.

Seismic Unwired: Cutting the Cable Can Help in Difficult Spots

Seismic Unwired David Monk said Apache Corp. uses wireless seismic receivers when it cites advantages over traditional systems connected together by cables. Examples offered by Apache’s worldwide director of geophysics include a prospect that straddled the border of Argentina and Chile where equipment and radio signals were not allowed to cross; a survey in the shallow waters of the Gulf of Mexico where production platforms would get in the way of streamers used to pick up seismic signals; onshore areas where the cost of crews is high, which is the case in much of the US and Canada; and the Cook Inlet where the extreme environment offshore and onshore made wireless the choice for a number of reasons. “These things are more efficient systems over more difficult terrain,” Monk said. At the time of the interview nearly all the seismic exploration projects for Apache were wireless. Eliminating the bright orange or yellow cables reduces the weight of the system, can make it easier to work around obstacles or in difficult waters, and can significantly reduce the profile of seismic exploration in areas where that activity may not be welcome. A case study by Geospace, a maker of wireless receivers, of a seismic shoot done on the plains of Colombia by Pacific Rubiales Energy Corp., concluded a crew of 21 could lay down the wireless seismic receivers that would have required workers if it had been wired. And a side-by-side comparison by Apache in the Cook Inlet showed the quality of the seismic data gathered on land was similar for wired and unwired receivers, but wireless performed far better offshore in an area known for its difficult tides and currents. Apache is a wireless pioneer and is far from the norm in an industry where the largest seismic receiver provider, Sercel, estimates 90% of the seismic channels in use are wired. But the rapid takeoff of wireless receiver sales suggests that is changing. In most cases one channel, with a geophone that detects the echoes used for underground mapping, is equal to one wireless unit. Wireless multichannel units, though, are a growing part of the market.

A Retrospective Evaluation of Sustainable Yields for Australia's Northern Prawn Fishery

ABSTRACTThe fundamental aim in fisheries management is to determine an optimal fishing effort for sustainably harvesting from a replenishable resource. The current management objective of Australia's Northern Prawn Fishery is to maximize the long‐term net economic return following Australian government policy, resulting in an average recent catch of tiger prawn species of about 1,250 tons only. However, the maximum sustainable catch stated from different studies is around 3,000–4,700 tons. We also evaluated the net profit assuming that there was no buyback scheme in 2005 and the fishing fleet was kept at 89 vessels since 2005 and concluded that 40% more catch on average (2006–2009) and an additional total profit of A$17 million (excluding crew cost) could have been gained in addition to the many millions of dollars of savings in the buyback scheme. These findings have great implications for future management in Australia and elsewhere because there is a grave concern of overfishing worldwide.

Estimating domestic US airline cost of delay based on European model

Researchers are applying more holistic approaches to the feedback control of the air transportation system. Many of these approaches rely on economic feedback, including the cost of delays to the airlines. Establishing an accurate mechanism for estimating the cost of a delays for each portion of a flight (gate costs, taxiing in and out costs, and en-route costs) is useful for many aspects of modeling airline behavior and for better understanding the likely impact of regulations.Cook et al. (2004) developed a rigorous methodology and collected data for estimating the components of airline delay costs for various segments of a scheduled flight. The model, based on confidential information from European airlines for 12 types of aircraft ca. 2003, was not transparent with regards to how each of the major components of cost (crew costs, fuel costs, maintenance, depreciation, etc.) impacted that total. This paper describes the development of an airline cost model, based on the Eurocontrol model. The airline cost model explicitly identifies the components of airline costs, is based on US airline cost data, and includes 111 aircraft types. The new model is designed to allow costs to be updated whenever the basic costs change. It considers the type of the aircraft when making calculations, both from the perspective of fuel burn and other costs and uses publically available data on burn rates and block-hour direct operating costs (BHDOC) to obtain these estimates. A case-study analysis of airline costs of operation at 19 major US airports is provided.

An Improved Genetic Algorithm for Crew Pairing Optimization

Crew pairing is a sequence of flights beginning and ending at the same crewbase. Crew pairing planning is one of the primary processes in airline crew scheduling; it is also the primary cost-determining phase in airline crew scheduling. Optimizing crew pairings in an airline timetable helps minimize operational crew costs and maximize crew utilization. There are numerous restrictions that must be considered and just as many regulations that must be satisfied in crew pairing generation. The most important regulations—and the ones that make crew pairing planning a highly constrained optimization problem—are the the limits of the flight and the duty periods. Keeping these restrictions and regulations in mind, the main goal of the optimization is the generation of low cost sets of valid crew pairings which cover all flights in the airline’s timetable. For this research study, We examined studies about crew pairing optimization and used these previously existing methods of crew pairing to develop a new solution of the crew pairing problem using genetic algorithms. As part of the study we created a new genetic operator—called perturbation operator.Unlike traditional genetic algorithm implementations, this new perturbation operator provides much more stable results, an obvious increase in the convergence rate, and takes into account the existence of multiple crewbases.

Maritime Community and its Human Resource Mobility

In the maritime community, a runner-up will undertake this typical process to catch up with the front runner; first, as a nation's economy grows its domestic crew costs rise, creating a gap with those abroad, which in turn depresses the international competitiveness of shipping companies. Then, to maintain their economic strength, shipping companies have their ships fly a “flag of convenience” relying on increasing amounts of cheap foreign labour. As a result, the nation gradually loses domestic seafarers, which, in the worst case, leads to a depletion of national human resource needed for its maritime cluster to continue to exist. In that sense, the personnel shortage issue is a fate for top runners in the marine transport world, where international competitiveness is inevitable. The Japanese maritime sector is just facing this issue. In this paper, the current situation in the maritime sector and its dependence on foreign labour, the cause and process of the change and the problems of the outcomes are explained, and the possible solutions in terms of the social mechanism of personnel development and utilization are discussed.

Flexible hiring in a make to order system with parallel processing units

In this paper, we study a make-to-order production system with parallel, identical processing units. Each order needs to be satisfied on a single processing unit that is run by a crew. The inter-arrival time and the service time for each order are random variables. The system operates under a lead time performance constraint, which demands the completion of each order within a pre-determined lead time with a certain probability. The minimum number of processing units needed to satisfy this constraint is determined at the tactical level. Our research focuses on the cost savings that can be realized with the use of flexible crews via contractual hiring agreements with an External Labor Supply Agency (ELSA). The ELSA can periodically provide an agreed number of crews. The cost incurred for a flexible crew is higher than that for a permanent crew, and is decreasing in the period length. We model and analyze this system using the transient behavior analysis of multi-server queues and propose several empirically testable functions for the cost of flexible crews. In our computational study, we demonstrate possible cost savings of 2-level, threshold type hiring policies, relative to the fixed capacity system, under 9 scenarios with three demand-to-processing rate ratios and three lead time performance constraints, each of which reflects a different level of ambition. We observe that the maximum savings occur when the cost of a flexible crew is same as that of a permanent crew, and range from 29.38% to 50.56%. However, as the flexible crews become more expensive, the system may choose to employ permanent crews only. We observe that cost savings consist of two parts: savings due to the cancellation of the sclerosis of capacity discreteness, and savings due to the use of workload information in hiring actions. The latter part is higher for more ambitious lead time performance constraints, and for higher mean processing times. Finally, when there is an additional cost for transacting an agreement with the ELSA, we observe that the capacity flexibility option loses its charm, especially if the transaction cost is higher than the cost of a permanent crew.

Optimization Approach to Air Crew Rostering Problem

The airline crew rostering problem consists of assignment of crews to planned round trips resulting in the construction of personalized monthly crew schedules called rosters. Airline companies have a monthly task of building these rosters for crews available with them. A mixed integer linear programming (MIP) formulation is presented to find an optimal solution. The objective of this formulation is to minimize the crew cost associated with the round trips and the cost of reserve crews, who remain idle throughout the scheduling horizon. Computational experiments were also carried to test the effectiveness of the heuristic for small size problems on randomly generated test data.

Optimization Approach to Air Crew Rostering Problem

The airline crew rostering problem consists of assignment of crews to planned round trips resulting in the construction of personalized monthly crew schedules called rosters. Airline companies have a monthly task of building these rosters for crews available with them. A mixed integer linear programming (MIP) formulation is presented to find an optimal solution. The objective of this formulation is to minimize the crew cost associated with the round trips and the cost of reserve crews, who remain idle throughout the scheduling horizon. Computational experiments were also carried to test the effectiveness of the heuristic for small size problems on randomly generated test data.

Optimizing Railway Crew Scheduling at DB Schenker

Freight railway crew scheduling consists of generating crew duties for operating trains on a schedule at minimal cost while meeting all work regulations and operational requirements. Typically, a freight railway operation uses thousands of trains and requires thousands of crew members to operate them. Because of the problem's large size, even moderate percentage savings in crew costs translate into large monetary savings. However, freight railway operations are complex, and a crew-scheduling problem is difficult to solve. We describe the development and implementation of crew-scheduling software at DB Schenker, the largest European railway freight carrier. The software is based on a column-generation solution technique. Computational results demonstrate that high-quality solutions can be obtained using reasonable run times, even for large problem instances. We implemented all of DB Schenker's major requirements to ensure that the software is operationally viable. Management also uses this software as a decision support tool for strategic planning.