Strategic planning in fractional aircraft ownership programs

In the fractional ownership model, the partial owner of an aircraft is entitled to certain flight hours per year, and the management company is responsible for all the operational considerations of the aircraft and for making an aircraft available to the owner at the requested time and place. In the recent years although the industry as a whole has experienced significant growth, most of the major fractional jet management companies have been unprofitable. To increase profitability a management company must minimize its operating costs and increase its crew and aircraft utilization. In this paper, we present a methodology for efficiently scheduling the available resources of a fractional jet management company that takes into consideration the details in real world situations. We then discuss several strategic planning issues, including aircraft maintenance, crew swapping, demand increase and differentiation, and analyze their effects on the resource utilization and profitability.     

A multi-depot period vehicle routing problem arising in the utilities sector

This paper considers the resource planning problem of a utility company that provides preventive maintenance services to a set of customers using a fleet of depot-based mobile gangs. The problem is to determine the boundaries of the geographic areas served by each depot, the list of customers visited each day and the routes followed by the gangs. The objective is to provide improved customer service at minimum operating cost subject to constraints on frequency of visits, service time requirements, customer preferences for visiting on particular days and other routing constraints. The problem is solved as a Multi-Depot Period Vehicle Routing Problem (MDPVRP). The computational implementation of the complete planning model is described with reference to a pilot study and results are presented. The solution algorithm is used to construct cost-service trade-off curves for all depots so that management can evaluate the impact of different customer service levels on total routing costs.     

Optimizing winter road maintenance operations under real-time information

This paper introduces a real-time optimization model that can be used by maintenance managers to develop and evaluate alternative resources allocation plans for winter road maintenance operations. The model takes into account a wide range of road and weather condition factors such as road network topology, road class, weather forecasts, and contractual service levels, and produces a vehicle dispatch schedule that is optimal with respect to operating costs and quality of service. The model is then used in an analysis on a realistic case to illustrate the potential impact of improved information on winter maintenance operations.     

Minimizing fleet operating costs for a container transportation company

This paper focuses on a fleet management problem that arises in container trucking industry. From the container transportation company perspective, the present and future operating costs to minimize can be divided in three components: the routing costs, the resource (i.e., driver and truck) assignment costs and the container repositioning costs (i.e., the costs of restoring a given container fleet distribution over the serviced territory, as requested by the shippers that own the containers).This real-world problem has been modeled as an integer programming problem. The proposed solution approach is based on the decomposition of this problem in three simpler sub-problems associated to each of the costs considered above.Numerical experiments on randomly generated instances, as well as on a real-world data set of an Italian container trucking company, are presented.     

A new MIP model for mine equipment scheduling by minimizing maintenance cost

Mining investment has been recognized as capital intensive due mainly to the cost of large equipment. Equipment capital costs for a given operation are usually within the order of hundreds of million dollars but may reach to billion dollars for large companies operating multiple mines. Such large investments require the optimum usage of equipment in a manner that the operating costs are minimized and the utilization of equipment is maximized through optimal scheduling. This optimum usage is required to ensure that the business remains sustainable and financially stable. Most mining operations utilize trucks to haul the mined material. Maintenance is one of the major operating cost items for these fleets as it can reach approximately one hundred million dollars yearly. There is no method or application in the literature that optimizes the utilization for truck fleet over the life of mine. A new approach based on mixed integer programming (MIP) techniques is used for annually scheduling a fixed fleet of mining trucks in a given operation, over a multi-year time horizon to minimize maintenance cost. The model uses the truck age (total hours of usage), maintenance cost and required operating hours to achieve annual production targets to produce an optimum truck schedule. While this paper focuses on scheduling trucks for mining operation, concept can be used in most businesses using equipment with significant maintenance costs. A case study for a large scale gold mine showed an annual discounted (10% rate) maintenance cost saving of over $2M and more than 16% ($21M) of overall maintenance cost reduction over 10 years of mine life, compared with the spreadsheet based approach used currently at the operation.     

Optimal maintenance of two stochastically deteriorating machines with an intermediate buffer

We consider a manufacturing system in which an input generating installation transfers a raw material to a subsequent production unit. Both machines deteriorate stochastically with usage and may fail. For each machine the deteriorating process is described by some known transition probabilities between different degrees of deterioration. A buffer has been built between the two machines in order to cope with unexpected failures of the installation. A discrete-time Markov decision model is formulated for the optimal preventive maintenance of both machines. The maintenance times are geometrically distributed and the cost structure includes operating costs, storage costs, maintenance costs and costs due to the lost production. It is proved that for fixed buffer content and for fixed deterioration degree of one machine, the average-cost optimal policy initiates a preventive maintenance of the other machine if and only if its degree of deterioration exceeds some critical level. We study, by means of numerical results, the effect of the variation of some parameters on the optimal policy and on the minimum average cost. For the case in which the maintenance times follow continuous distributions, an approximate discrete-time Markov decision model is proposed.     

A mathematical programming model for integrating production and procurement transport decisions

In this paper, we propose a new mathematical programming model for integrating production and procurement transport planning decisions in manufacturing systems in a unique optimization model. This problem was introduced conceptually and dubbed as MRP IV by Díaz-Madroñero et al. (2012) to extend the current MRP (material requirement planning) systems. This proposal simultaneously considers material, production resources capacities and procurement transport planning decisions with different shipping modes (such as full-truckload, less-than-truckload and milk-run) in the supply chain to avoid suboptimal results, which are usually generated due to sequential and independent plans. We considered an industrial automobile company to validate the proposed model using real world data. The results obtained by the MRP IV proposed model, in terms of total planning costs and transport efficiency indicators, are better than those obtained in the current heuristic procedures followed in the company under study.     

Production Planning in the New Zealand Dairy Industry

From 1977 onwards, D.S.I.R. has been developing an L.P. model to help the largest N.Z. dairy company plan its medium-term production. This time-staged model finds the most profitable daily production schedule of the various powder, casein, cheese and butter products. Computer reports and graphics show Company management how to allocate the milk available in the various farming regions to the Company's factories, and where to send the by-products for further processing.The L.P. models seasonal fluctuations in wholemilk availability and quality, as well as transport costs, factory capacities and costs, and product-yields and prices. Comparison runs have shown that the L.P. increases the profitability of the manual plan by over $5000 per day (because the computer can handle changing yields, factory costs and by-product processing). The model gives management the ability to adjust production plans quickly in response to improved information, new market opportunities and emergencies like plant breakdown.     

A mathematical model and algorithms for the aircraft hangar maintenance scheduling problem

An aircraft hangar maintenance scheduling problem is studied, motivated by the aircraft heavy maintenance conducted in a hangar operated by an independent maintenance service company. The aircraft hangar maintenance scheduling problem in such context consists of determining a maintenance schedule with minimum penalty costs in fulfilling maintenance requests, and a series of hangar parking plans aligned with the maintenance schedule through the planning period. A mixed-integer linear programming (MILP) mathematical model, integrating the interrelations between the maintenance schedule and aircraft parking layout plans, is presented at first. In the model, the variation of parking capacity of the maintenance hangar and the blocking of the aircraft rolling in and out path are considered. Secondly, the model is enhanced by narrowing down the domain of the time-related decision variables to the possible rolling in and out operations time of each maintenance request. Thirdly, to obtain good quality feasible solutions for large scale instances, a rolling horizon approach incorporating the enhanced mathematical model is presented. The results of computational experiments are reported, showing: (i) the effectiveness of the event-based discrete time MILP model and (ii) the scalability of the rolling horizon approach that is able to provide good feasible solutions for large size instances covering a long planning period.     

Supply chain design considering economies of scale and transport frequencies

In this paper we consider a 3-echelon, multi-product supply chain design model with economies of scale in transport and warehousing that explicitly takes transport frequencies into consideration. Our model simultaneously optimizes locations and sizes of tank farms, material flows, and transport frequencies within the network. We consider all relevant costs: product cost, transport cost, tank rental cost, tank throughput cost, and inventory cost. The problem is based on a real-life example from a chemical company. We show that considering economies of scale and transport frequencies in the design stage is crucial and failing to do so can lead to substantially higher costs than optimal. We solve a wide variety of problems with branch-and-bound and with the efficient solution heuristics based on iterative linearization techniques we develop. We show that the heuristics are superior to the standard branch-and-bound technique for large problems like the one of the chemical company that motivated our research.     

An Interactive Planning Model for the New Zealand Dairy Industry

A long-term planning model for a large New Zealand dairy company is described. The model presents an integrated view of the company's operation, including transportation and processing. The model used is based on a network formulation, NETPLAN, developed by the authors to carry out the optimisation. NETPLAN is highly flexible, interactive and provides graphical output of the results. The optimisation maximises net revenue based on product prices, variable process costs and variable transport costs subject to factory capacity, product demand and raw material supply constraints.     

Warehouse location with production,inventory, and distribution decisions: a case study in the lube oil industry

In this paper, a supply chain management problem from a real case study is modeled and solved. A company in Pakistan wanted to outsource part of its warehousing activity to a third party logistics (3PL) provider. Consequently, the company had to decide on where to rent space in the 3PL warehouses. Knowing that such a strategic decision is affected by tactical and operational decisions, the problem is presented as a facility location problem integrating production, inventory, and distribution decisions. The problem is formulated as a mixed integer linear programming model which minimizes the total cost composed of location, distribution, production, and inventory costs. Several constraints specific to the situation and policy of the company were considered. A thorough analysis was done on the results obtained with respect to formulation efficiency, sensitivity analysis, and distribution of costs. In addition to the solution of the company problem, a set of 1215 problem instances was generated by varying five types of relevant costs in a full factorial manner. The solution of the generated problems always suggests to open in the same two locations and the integrality gaps averaged 0.062 % with a maximum of 0.102 %. On average, the major components of the total cost are production cost (96.6 %), transportation costs (2.7 %), and inventory holding costs (0.38 %). The total warehouse opening cost accounted for less than 0.05 % of the total costs.     

Optimal economic production quantity policy for imperfect process with imperfect repair and maintenance

This study integrates maintenance and production programs with the economic production quantity (EPQ) model for an imperfect process involving a deteriorating production system with increasing hazard rate: imperfect repair and rework upon failure (out of control state). The imperfect repair performs some restorations and restores the system to an operating state (in-control state), but leaves its failure until perfect preventive maintenance (PM) is performed. There are two types of PM, namely imperfect PM and perfect PM. The probability that perfect PM is performed depends on the number of imperfect maintenance operations performed since the last renewal cycle. Mathematical formulas are obtained for deriving the expected total cost. For the EPQ model, the optimum run time, which minimizes the total cost, is discussed. Various special cases are considered, including the maintenance learning effect. Finally, a numerical example is presented to illustrate the effects of PM, setup, breakdown and holding costs.     

考虑质物耗损的银行存货质押融资决策研究

在存货需求随机波动下,为研究存货耗损对存货质押融资过程中各方决策的影响,构建由银行、中小企业和第三方物流企业(Third-Part Logistics, TPL)组成的存货质押融资系统。在考虑银行下侧风险控制和企业还贷能力下,以实现银行利润最大化为目标建立模型。分析初始耗损率、激励因子、耗损改善因子和市场需求对质押率和银行利润的影响。研究表明:(1)银行利润与质物耗损率呈负相关,银行有激励TPL提高服务水平,降低耗损率的动力。(2)银行激励TPL降低耗损率有助于银行提高质押率并拓宽质物的选择范围。(3)仅当初始耗损率超过一定限值时,银行激励带来的额外收益才会高于激励成本。最后通过数值实验进行验证,从而为银行的存货质押融资决策提供指导。     

Queueing Theory in the Solution of a Transport Evaluation Problem

The problem of minimizing the overall cost of operating the internal transport system of a steelworks is examined. The paper describes the practical problem encountered by an OR team and the approach that was adopted in the subsequent study. This approach led to the development of a simple queueing model of the rail transport system, which accounted for 90 per cent of the weight of material moved within the steelworks complex. The model was used to evaluate alternative methods of operating and controlling the rail transport system. The findings of the study were implemented and some of the operational details are outlined in the paper. Savings of at least 10 per cent in operating costs were achieved by the study.Hence this paper presents a detailed case study of a comprehensive approach to a transport planning and evaluation problem.     

Scheduling of road vehicles in sugarcane transport: A case study at an Australian sugar mill

Pressure to remain internationally competitive has forced Australian sugar mills to reduce capital and operational costs. Improved scheduling of road transport vehicles provides one such opportunity, as it would reduce vehicle queue and mill idle times and hence the number of vehicles needed. It is difficult for mill traffic officers to produce good transport schedules manually due to the need to service a large number of harvesters in different locations. To address this issue, research was undertaken participatively with a sugar milling company in Australia to produce and implement a mixed integer programming model that represents the road transport operations. Two meta-heuristics were applied to find a solution to the model, leading to potential cost savings of AU$240,000 per year versus schedules produced manually by the mill traffic officer. The model was also applied to explore regional planning options for a more integrated harvesting and transport system.     

The use of state space relaxation for the dynamic facility location problem

Dynamic facility location is concerned with developing a location decision plan over a given planning horizon during which changes in the market and in costs are expected to occur. The objective is to select from a list of predetermined possible facility sites the locations of the facilities to use in each period of the planning horizon to minimise the total costs of operating the system. The costs considered here include not only transport and operation/maintenance charges but also relocation costs arising from the opening and closing of facilities as required by the plan.The problem is formulated in terms of dynamic programming but for simplicity with restrictions on the numbers of facilities that can be opened in a given period. The problem was solved using both dynamic programming and a branch and bound approach using state space relaxation. These two approaches are contrasted with different data and with different assumptions to compare the influence of alternative factors on the computational efficiency of both solution methods.     

A multiple period capacitated inventory model for airline fuel management: a case study

One of the major operating cost items of an airline company is fuel, which can amount to approximately 20% of its overall operating cost. This paper presents a decision support model that determines the amount of fuel to be uplifted by a plane at each station along its route over a predetermined planning horizon so as to minimise overall fuel costs. The aforementioned fuel management problem is modelled as a multiple period capacitated inventory problem and solved using linear programming. An example application illustrates the applicability of this model to Middle East Airline's (MEA) operations and summarises the dollar savings obtained by applying it over a one week planning horizon.     

Sell through a local retailer or operate your own store? Channel structure and risk analysis

Either a company store or a local retailer can be used to establish a sales channel. For high-value products with an existing competing brand, this choice represents a crucial decision a brand-named manufacturer must make for a new market. Under the burden of high operating costs, a weak local retailer may find it difficult to sustain and using it may hurt the manufacturer’s chance to successfully establish the channel. We consider a chain-to-chain competition model comprising two manufacturers and two retailers, in which one retailer may be unable to continue its operation because of high financing costs. We identify a threshold policy for the manufacturers to select the channel structure. Interestingly, we find that channel integration is not always better. Without the consideration of contract termination risk, the manufacturer will bear the operating expenses when its opportunity cost is low or the retailer’s financing cost is sufficiently high. In equilibrium, the manufacturers will choose either (decentralized, decentralized) or (integrated, integrated) channel structure. However, when the termination risk is considered, the equilibrium channel structure would be more likely (integrated, integrated) or (integrated, decentralized).     

A robust optimization model for agile and build-to-order supply chain planning under uncertainties

Supply chain planning as one of the most important processes within the supply chain management concept, has a great impact on firms’ success or failure. This paper considers a supply chain planning problem of an agile manufacturing company operating in a build-to-order environment under various kinds of uncertainty. An integrated optimization approach of procurement, production and distribution costs associated with the supply chain members has been taken into account. A robust optimization scenario-based approach is used to absorb the influence of uncertain parameters and variables. The formulation is a robust optimization model with the objective of minimizing the expected total supply chain cost while maintaining customer service level. The developed multi-product, multi-period, multi-echelon robust mixed-integer linear programming model is then solved using the CPLEX optimization studio and guidance related to future areas of research is given.