Journal of the Operational Research Society

Suman, B; Kumar, P

doi: 10.1057/palgrave.jors.2602068pmid: N/A

AbstractThis paper presents a comprehensive review of simulated annealing (SA)-based optimization algorithms. SA-based algorithms solve single and multiobjective optimization problems, where a desired global minimum/maximum is hidden among many local minima/maxima. Three single objective optimization algorithms (SA, SA with tabu search and CSA) and five multiobjective optimization algorithms (SMOSA, UMOSA, PSA, WDMOSA and PDMOSA) based on SA have been presented. The algorithms are briefly discussed and are compared. The key step of SA is probability calculation, which involves building the annealing schedule. Annealing schedule is discussed briefly. Computational results and suggestions to improve the performance of SA-based multiobjective algorithms are presented. Finally, future research in the area of SA is suggested.

Kirby, M W

doi: 10.1057/palgrave.jors.2602078pmid: N/A

AbstractAn essential component of the history of Operational Research (OR) in Britain is the institutional development of the discipline. In this respect, a defining element is the debate on the issue of professionalism, which took place within the Operational Research Society (ORS) in the later 1960s and 1970s. For the historian, the debate provides major insights into the composition of the OR community at a critical stage in its development following on the sustained expansion of ORS membership in the 1960s. As this article reveals, the proposed movement of the ORS from ‘learned society’ to ‘professional’ status proved to be a deeply divisive issue, with a hard core of ORS members, both academics and practitioners, combining to resist the recommendations of the contemporary ORS Council and the leading officers of the Society. The article focuses on the debates on what one protagonist viewed as ‘a festering sore’ in the history of the ORS. In this respect, it provides a prologue to a second article commenting on the origins and results of the recent decision of the ORS Council to establish a professional membership grade—‘Fellow of the Operational Research Society’.

Lezaun, M; Pérez, G; Sáinz de la Maza, E

doi: 10.1057/palgrave.jors.2602088pmid: N/A

AbstractIn this paper, we present an applied study commissioned by Metro Bilbao on how to establish a more egalitarian annual allocation of work to drivers. Task allocation is mixed, with some tasks allocated on a rotating basis and others not. The model proposed is solved as a sequence of four types of integer programming problem. The solution obtained is quasi-optimal: all drivers carry out practically the same tasks over the full year. The main contribution of this paper is its method for combining semi-rotating allocation with a planning time frame divided into five periods of three different types with a workload distributed in a non uniform fashion over the days of the week, and with constraints agreed with employees to obtain an egalitarian solution. This method is being implemented at Metro Bilbao, and Eusko Tren has commissioned a study into a similar method by the authors.

Andreeva, G

doi: 10.1057/palgrave.jors.2602091pmid: N/A

AbstractCredit scoring discriminates between ‘good’ and ‘bad’ credit risks to assist credit-grantors in making lending decisions. Such discrimination may not be a good indicator of profit, while survival analysis allows profit to be modelled. The paper explores the application of parametric accelerated failure time and proportional hazards models and Cox non-parametric model to the data from the retail card (revolving credit) from three European countries. The predictive performance of three national models is tested for different timescales of default and then compared to that of a single generic model for a timescale of 25 months. It is found that survival analysis national and generic models produce predictive quality, which is very close to the current industry standard—logistic regression. Stratification is investigated as a way of extending Cox non-parametric proportional hazards model to tackle heterogeneous segments in the population.

Guarnieri, J; Johnson, A W; Swartz, S M

doi: 10.1057/palgrave.jors.2602101pmid: N/A

AbstractCombat aircraft operations are usually constrained by limits on the logistics resources available. However, models that can compute the logistics resources necessary to support planned combat aircraft activity typically are custom applications that are data-intensive and difficult to use. This paper introduces a method for the Argentine Air Force (AAF) to estimate the mean number of aircraft that can be restored in a given time between consecutive sorties, given specified maintenance resources and base physical geometry. This maintenance resources evaluation technique (MRET) uses an analytical approach to estimate the mean and variance of aircraft unscheduled downtime. These parameters are then used in a Monte Carlo simulation of scheduled and unscheduled maintenance tasks necessary to prepare aircraft for the next sortie. When programmed in a spreadsheet, the MRET combines a high response speed with a moderately detailed scenario description, making the model suitable for the AAF.

Tavana, M

doi: 10.1057/palgrave.jors.2602107pmid: N/A

AbstractAnalog missions are real-life, Earth-based science missions whose purpose is to help understand the operations, techniques, and technologies required to perform similar tasks during future human spaceflight missions. The goal of performing an analog mission is to prepare crewmembers and support teams for future space missions in a low risk, low-cost environment. Vehicle, habitat, and surface terrain simulators are used to test hardware, operations, and tasks repeatedly for analog missions. This study presents a multi-criteria decision making model that was developed for the Integrated Human Exploration Mission Simulation Facility project at Johnson Space Center to assess the priority of a set of human spaceflight mission simulators. The proposed framework integrates subjective judgments derived from the analytic hierarchy process with entropy data into a preference model to prioritize five mission simulators for the human exploration of Mars.

Huang, J-J; Tzeng, G-H; Ong, C-S

doi: 10.1057/palgrave.jors.2602108pmid: N/A

AbstractSynergy effects are the motives to enter into strategic alliances; however due to lack of adequate preparation or planning, these alliances often fail. It is of no doubt that a successful strategic alliance depends on choosing the correct alliance partners and appropriate resource allocation. In this paper, the fuzzy multi-objective dummy programming model is proposed to overcome the above-mentioned problems. Two types of strategic alliances, joint ventures and mergers and acquisitions (M&A), are demonstrated to choose the best alliance partners and allocate the optimal alliance resources in a numerical example. Based on the results, our method can provide the optimal alliance cluster and satisfaction in strategic alliances.

Saunders, J; Jobber, D; Mitchell, V

doi: 10.1057/palgrave.jors.2602053pmid: N/A

AbstractIncreasing mail-survey response using monetary incentives is a proven, but not always cost-effective method in every population. This paper tackles the questions of whether it is worth using monetary incentives and the size of the inducement by testing a logit model of the impact of prepaid monetary incentives on response rates in consumer and organizational mail surveys. The results support their use and show that the inducement value makes a significant impact on the effect size. Importantly, no significant differences were found between consumer and organizational populations. A cost–benefit model is developed to estimate the optimum incentive when attempting to minimize overall survey costs for a given sample size.

Kim, H-J; Lee, D-H; Xirouchakis, P

doi: 10.1057/palgrave.jors.2602094pmid: N/A

AbstractThis paper considers the problem of determining the disassembly schedule (quantity and timing) of products in order to satisfy the demand of their parts or components over a finite planning horizon. The objective is to minimize the sum of set-up, disassembly operation, and inventory holding costs. As an extension of the uncapacitated versions of the problem, we consider the resource capacity restrictions over the planning horizon. An integer program is suggested to describe the problem mathematically, and to solve the problem, a heuristic is developed using a Lagrangean relaxation technique together with a method to find a good feasible solution while considering the trade-offs among different costs. The effectiveness of the algorithm is tested on a number of randomly generated problems and the test results show that the heuristic suggested in this paper can give near optimal solutions within a short amount of computation time.

González-Pachón, J; Romero, C

doi: 10.1057/palgrave.jors.2602103pmid: N/A

AbstractThis paper proposes a procedure for aggregating individual cardinal utility functions into a social utility function that represents the preferences of all the individuals as a whole. The procedure is non-interactive and is based upon the determination of the utility consensus values. This is accomplished by minimizing a distance function model that is transformed into an Archimedean goal programming problem. The procedure is applied to a general group multilinear utility function.