An orienteering model for the search and rescue problem

In this paper, we propose a new model for the search and rescue problem. We focus on the case of a single airborne search asset through a connected space and continuous time with a maximum travel time \(T\) . The intent is to maximize the detection of a cooperative target (search and rescue). The proposed model is based on the assumption of existing a priori information (e.g., result of information fusion process) to establish a spatial distribution of probability of containment in possible geographic locations. The possibility area is defined using a cut threshold on the probability of containment and the search path as well as the allocation of the level of effort to each region in the search space is obtained based on an orienteering model. We illustrate the application of the proposed model on an empirical example.     

A model to optimize placement operations on dual-head placement machines

Dual-head placement machines are important in the assembly of circuit cards because they offer the capability to place large components accurately. This paper presents a novel column-generation approach for optimizing the placement operations of a dual-head placement machine with the ultimate goal of improving the efficiency of assembly operations. Research objectives are a model that reflects relevant, practical considerations; a solution method that can solve instances within reasonable run times; and tests to establish computational benchmarks. Test results demonstrate the efficacy of our optimization approach on problems of realistic size and scope.     

A dynamic multi-objective location-allocation model for search and rescue assets

This paper presents a dynamic multi-objective mixed integer linear programming model to optimize the location and allocation of search and rescue (SAR) boats and helicopters to enhance the performance of maritime SAR missions. Our model incorporates simulated incident scenarios to account for demand uncertainty and allows relocation of vessels seasonally. We define three objectives as responding to incidents within a critical time, generating a balanced workload distribution among vessels of various types, and minimizing costs associated with operations and vessel relocations. Implementing a goal programming approach, we solve the problem for various objective function term weights and compare the performance of each solution with respect to 10 different metrics. Using historical incident datasets for the Aegean Sea, we show that the proposed model and solution approach can significantly improve the SAR performance and provide decision support for planners in developing effective and efficient resource location-allocation schemes.     

An investigation of open-loop and inverse simulation as nonlinear model validation tools for helicopter flight mechanics

The nonlinear model validation techniques of open-loop and inverse simulation are introduced. The methodologies are explained and examples are given. The paper presents the results of an investigation into the use of open-loop and inverse simulation to help in the development of a nonlinear real-time helicopter model. The individual rigid body state equations in the model are simulated with the aim of producing insight into the cause of inaccuracies in the model. A suspected source of inaccuracy is verified using partial open-loop simulation. Unmodelled dynamics are represented by using the relevant flight data as an open-loop input to the simulation thus revealing the effect of incorporating those dynamics. After localising the cause of inaccuracies in the simulation model, modifications and improvements are verified using closed-loop simulation. The improvements are then evaluated by comparing results in normal and inverse simulation modes.     

An ILP model with logical constraints for mail sorting facility selection

This paper studies a facility selection problem which is generalised from the design of a mail sorting system with multiple input and output. The problem is formulated as a 0–1 integer linear programming (ILP) problem with logical constraints. We show how the logical constraints can be embedded into a ILP model. We compare three strategies for handling logical relations: (1) explicitly as added linear constraints; (2) implicitly as symbolic constraints; and (3) a combination of the two. The effectiveness of computations under different strategies are shown.     

An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations

This study develops a mathematical model for helicopter mission planning during a disaster relief operation. The decisions inherent in the problem decompose hierarchically into two sub-problems where tactical decisions are made at the top level, and the operational routing and loading decisions are made at the base level. Consistency between the decomposed problems is achieved with an iterative coordination procedure which transfers anticipated information from the base level to improve the top level decisions. The existence of conflicting multiple objectives in this hierarchical structure requires the development of a multi-criteria analysis, and an interactive procedure is designed with the top level decision-maker to assess the preference of alternative non-dominated solutions.     

An objective hyperplane search procedure for solving the general all-integer linear programming (ILP) problem

We describe an objective hyperplane search method for solving a class of integer linear programming (ILP) problems. We formulate the search as a bounded knapsack problem and develop requisite theory for formulating knapsack problems with composite constraints and composite objective functions that facilitate convergence to an ILP solution. A heuristic solution algorithm was developed and used to solve a variety of test problems found in the literature. The method obtains optimal or near-optimal solutions in acceptable ranges of computational effort.     

Applying neural network and scatter search to optimize parameter design with dynamic characteristics

Parameter design is critical to enhancing a system's robustness by identifying specific control factor set points (levels) that make the system least sensitive to noise. Engineers have conventionally applied Taguchi methods to optimize parameter design. However, Taguchi methods can only obtain the optimal solution among the specified control factor levels. They cannot identify the real optimum when the parameter values are continuous. This study proposes a hybrid procedure combining neural networks and scatter search to optimize the continuous parameter design problem. First, neural networks are used to simulate the relationship between the control factor values and corresponding responses. Second, scatter search is employed to obtain the optimal parameter settings. The desirability function is utilized to transform the multiple responses into a single response. A case with dynamic characteristics is carried out in blood glucose strip manufacturing in Taiwan to demonstrate the practicability of the proposed procedure.     

An approach to optimize block surgical schedules

We provide an approach to optimize a block surgical schedule (BSS) that adheres to the block scheduling policy, using a new type of newsvendor-based model. We assume that strategic decisions assign a specialty to each Operating Room (OR) day and deal with BSS decisions that assign sub-specialties to time blocks, determining block duration as well as sequence in each OR each day with the objective of minimizing the sum of expected lateness and earliness costs. Our newsvendor approach prescribes the optimal duration of each block and the best permutation, obtained by solving the sequential newsvendor problem, determines the optimal block sequence. We obtain closed-form solutions for the case in which surgery durations follow the normal distribution. Furthermore, we give a closed-form solution for optimal block duration with no-shows.     

A simulation architecture to support intratheater sealift operations

A new architecture for simulating intratheater sealift operations is presented. Intratheater sealift operations refer to new strategies proposed for quickly deploying a military force to a theater of war when major seaports are not available. In this strategy, a self-deployable force is transported to a sea-based intermediate staging base (SISB) by conventional cargo transport ships. The SISB is a world-class seaport generally located within 800 miles of the theater of war. At the SISB, cargo is transferred to a new ship platform called the theater support vessel (TSV). TSVs are to be designed to access very small ports located at or near the theater of war. Simulation provides an efficient and cost-effective method for testing these strategies and for evaluating the required new logistics technologies. Should intratheater sealift operations prove viable, the simulation also provides a means to plan and rehearse an exercise. The new simulation architecture is described and example simulation case studies are conducted to demonstrate the capabilities and potential benefits of the approach.     

Development of a three-echelon SC model to optimize coordination costs

The purpose of this study is to suggest a conceptual framework for aligning the strategic issues and the structural issues of supply chain management, and also to disclose the effect of E-business application on such an alignment. The number of suppliers, number of tiers, the level of SC integration, order penetration point, lead time, and safety stock are defined as supply chain structural issues, and the characteristics of traded products and buyer–supplier relationship are set as key strategic issues for efficient construction of supply chain structure. E-business application is designed as a moderate variable for the alignment between the strategic issues and the structural issues of supply chain management. Such effort suggests a conceptual framework required for developing an advisable set of E-business application strategies for the efficiency improvement of overall supply chain management. The empirical research model proposed in this work may be used to establish an E-supply chain progression paradigm and a new dimensional manufacturing strategy framework in the E-business era.     

An integer programming approach to optimize Housing Benefit data retrieval

This article presents an integer programming approach to a practical problem faced by analysts in the Department for Work and Pensions working with Housing Benefit (HB) data. It shows how, using a simple modification of the set covering problem, the time required to retrieve HB data from the data server can be significantly decreased. Computational comparisons with two alternative, suboptimal approaches are also presented.     

An auction model arising from an Internet search service provider

Most search service providers such as Lycos and Google either produce irrelevant search results or unstructured company listings to the consumers. To overcome these two shortcomings, search service providers such as GoTo.com have developed mechanisms for firms to advertise their services and for consumers to search for the right services. To provide relevant search results, each firm who wishes to advertise at the GoTo site must specify a set of keywords. To develop structured company listings, each firm bids for priority listing in the search results that appear on the GoTo site. Since the search results appear in descending order of bid price, each firm has some control over the order in which the firm appears on the list resulting from the search. In this paper, we present a one-stage game for two firms that captures the advertising mechanism of a search service provider (such as GoTo). This model enables us to examine the firm’s optimal bidding strategy and evaluate the impact of various parameters on the firm’s strategy. Moreover, we analyze the conditions under which all firms would increase their bids at the equilibrium. These conditions could be helpful to the service provider when developing mechanisms to entice firms to submit higher bids.     

Autonomous change of behavior for environmental context: An intermittent search model with misunderstanding search pattern

Although foraging patterns have long been predicted to autonomously adapt to environmental conditions, empirical evidence has been found in recent years. This evidence suggests that the search strategy of animals is open to change so that animals can flexibly respond to their environment. In this study, we began with a simple computational model that possesses the principal features of an intermittent strategy, ie, careful local searches separated by longer steps, as a mechanism for relocation, where an agent in the model follows a rule to switch between two phases, but it could misunderstand this rule, ie, the agent follows an ambiguous switching rule. Thanks to this ambiguity, the agent's foraging strategy can continuously change. First, we demonstrate that our model can exhibit an autonomous change of strategy from Brownian‐type to Lévy type depending on the prey density, and we investigate the distribution of time intervals for switching between the phases. Moreover, we show that the model can display higher search efficiency than a correlated random walk.     

An improved Serre model: Efficient simulation and comparative evaluation

The so-called Serre or Green and Naghdi equations are a well-known set of fully nonlinear and weakly dispersive equations that describe the propagation of long surface waves in shallow water. In order to extend its range of application to intermediate water depths, some modifications have been proposed in the literature. In this work, we analyze a new Serre model with improved linear dispersion characteristics. This new Serre system, herein denoted by Serre_{α, β}, presents additional terms of dispersive origin, thus extending its applicability to more general depth to wavelength ratios.A careful development of the Serre_{α, β} model allows a straightforward and efficient numerical implementation. This model is suitable for numerical integration by a splitting strategy which requires the solution of a hyperbolic problem and a dispersive problem. The hyperbolic part is discretized using a high-order finite volume method. For the dispersive part standard finite differences are used. A set of numerical experiments are conducted to validate the Serre_{α, β} model and to test the robustness of our numerical scheme. Theoretical solutions and benchmark experimental data are used. Moreover, comparisons against the classical Serre equations and against another well established Serre model with improved dispersion characteristics are also made.     

An agent-based simulation model to evaluate alternative co-payment scenarios for contributing to health systems financing

Ageing populations, rapid technological progress and recent public budget cuts currently threaten the sustainability of public health systems. To meet growing needs with declining resources, decision-makers must identify new ways to avoid reducing the quality of services offered to citizens. This paper focuses on the so-called “co-payment” tools aimed to obtain additional resources for the public health budget directly from citizens. Whereas certain forms of co-payments have always been introduced within health systems to prevent moral hazard behaviours, other co-payment mechanisms are explicitly intended to help finance public healthcare systems. Literature and empirical findings do not agree about the final impact of such co-payment tools, particularly whether they can attain system sustainability and guarantee equitably delivered services. In this paper, we develop an agent-based simulation model which can be used by decision-makers as a decision support tool to compare different co-payment rules and evaluate their impact on the public budget and the health expense of different groups of citizens.     

An improved reservoir simulation model in the petroleum industry

Sensible prediction of petroleum production from a well reliesheavily on the accurate determination of reservoir constantsduring pressure drawdown or build-up tests. Models for simulatinga fractured reservoir have been developed to accommodate theslope changes in the measured pressure curves. This paper presentsa modification to Barenblatt et al.s (1960) prototype, suitablefor the simulation of a fractured reservoir. The modificationis intended to provide an improved interpretation of fluid flowin fractured porous media, as compared to the traditional conceptualization.The significant differences in terms of reservoir pressure predictionbetween this model and the one suggested by Warren & Root(1963) are identified and shown to depend on the compressibilitymagnitudes of fractures and matrix blocks. The analytical solutionsof this improved model have been obtained for both the caseof radial flow with quasi-steady matrix flow, and for the caseof one-dimensional linear flow where transient matrix flow isretained.