Airline fleet assignment concepts, models, and algorithms

Flexibility in reverse logistics: a framework and evaluation approach

The share of gross domestic product from the service industry reflects the competitiveness of a nation; the service industry in the USA accounts for around 80% of its gross domestic product, and it has been increasing gradually. Continual innovations and advances in enabling technologies for the service industry are crucial for developed countries to sustain their leading positions in the globalized economy. To clarify future research directions of operations research (OR) in the service industry, the state of art of OR has been examined systematically, the new requirements of OR are identified for its applications in service industries in comparison with those in manufacturing industries, and the limitations of existing methodologies and tools have been discussed. This paper was intended to provide an updated review on how OR has been applied in the service sector in recent years and what directions the study of OR will be carried forward in the near future. Under a proposed research framework, recent OR-related articles were collected from 17 leading OR journals and classified into the five most active sectors, that is, transportation and warehousing, information and communication, human health and social assistance, retails and wholesales, and financial and insurance services. The conclusions on the limitations of existing studies and the demanding ORs in the service have been drawn from our summaries and observations from a comprehensive review in this field. Copyright © 2013 John Wiley & Sons, Ltd.

Operations Research (OR) in Service Industries: A Comprehensive Review

https://espace.library.uq.edu.au/view/UQ:724143/UQ724143_OA.pdf

Pricing decisions for substitutable products with green manufacturing in a competitive supply chain

A classification of the literature on the planning of substitutable products

Optimal capacity for substitutable products under operational postponement

The ability to effectively match supply and demand under uncertainty can result in significant revenue benefits in the airline industry. We study the benefits of a Demand Driven Swapping (DDS) approach that takes advantage of the flexibilities in the system and dynamically swaps aircraft as departures near and more accurate demand information is obtained. We analyze the effectiveness of different DDS strategies, characterized by their frequency (how often the swapping decision is revised), in hedging against demand uncertainty. Swapping aircraft several weeks prior to departures will not cause much disturbance to revenue management and operations, but will be based on highly uncertain demands. On the other hand, revising the swapping decision later will decrease the possibility of bad swaps, but at a higher cost of disrupting airport services and operations. Our objective is to provide guidelines on how the flexible (swappable) capacity should be managed in the system. We study analytical models to gain insights into the critical parameters that affect the revenue benefits of the different swapping strategies. Our study determines the conditions under which each of the different DDS strategies is effective. We complement our analysis by testing the proposed DDS strategies on a set of flight legs, using data obtained from United Airlines. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.

Strategies for managing the flexible capacity in the airline industry

We study the capacity, pricing, and production decisions of a monopolist producing two substitutable products with flexible capacity. Although the capacity decision needs to be made ex ante, under demand uncertainty, pricing and production decisions can be postponed until after uncertainty is resolved. We show how key demand parameters (the nature of uncertainty, market size, and market risk) impact the optimal capacity decision under the linear demand function. In particular, we show that if the demand shock is multiplicative, then in terms of the “invest or not” decision, the firm will be immune to forecast errors in parameters of the underlying demand distribution. Furthermore, incorrectly modeling the demand shock as additive, when, in fact, it is multiplicative, may lead to overinvestment. On the other hand, although the concept of a growth in market size leads to similar conclusions under both additive and multiplicative demand shocks, how market risk affects the optimal capacity decision depends cr...

Optimal Capacity, Product Substitution, Linear Demand Models, and Uncertainty

Logistics and supply chain management play an important role in Thailand industry. We believed that logistics and supply chain management could be a means to improve competitive performance in service sector. This paper diagnoses the hospital's internal supply chain and logistics system in Thailand by business process analysis. This paper also investigates the inventory policy. Our results show the unconnected link at the case study's internal supply chain in the medicine inventory system between medicine storeroom in each ward, central warehouse and the hospital purchasing department. 'MSale' is used to represent average monthly demand; however, it does not reflect the end customer. This leads to inaccurate reorder point and order quantity at the central warehouse. The paper illustrates the business process analysis by using Integration Definition (IDEF0). The re-engineering business process will be proposed. Finally a new inventory system and software development for connecting this internal supply chain is presented.

Supply chain management in health sector in Thailand: a case study

This paper concerns a location problem which arises from an auto insurance company which aims to meet customers’ satisfaction by sending their surveyors to accident locations as promptly as possible. The goal of the problem is to find a suitable set of locations at which the surveyors stand by and to determine coverage area for each standby location by using heuristic algorithms. One challenge of this problem is that the number and locations of accidents can vary from time to time and may not be evenly distributed over a given time horizon. In this paper, a computational study is conducted to make a comparison between standby location planning strategies that involve one and two plans. For the strategies with two plans, several strategies for deciding when to switch between the plans are investigated. Experimental studies suggest that using multiple standby location plan throughout the time horizon can improve the efficiency of surveyors in terms of their total distance. Moreover, compared with usual rules of splitting dates such as weekdays versus weekends, the total distance can be reduced by switching between the location plans according to classification of dates by k-means clustering based on historical data of accident frequencies on each day. Keywords—Systems Theory, Signal Processing, classification, insurance company, k-means clustering, location problem, p-median, surveyor.

/pdf/heuristic-algorithms-for-surveyor-standby-location-planning-3eioxdq2v1.pdf

Rawee Suwandechochai

Papers

Optimal capacity for substitutable products under operational postponement

Strategies for managing the flexible capacity in the airline industry

Optimal Capacity, Product Substitution, Linear Demand Models, and Uncertainty

Supply chain management in health sector in Thailand: a case study

Heuristic Algorithms for Surveyor Standby Location Planning with Multiple Plans