University timetabling by constraint-based reasoning: A case study

This paper presents a case-study which applies constraint-based reasoning to university timetable planning. The timetabling problem is formulated as a constraint satisfaction model and this model is solved using constrained-directed search algorithms with built-in forward checking and constraint propagation. The model and algorithms were tested with real data containing 536 lessons to be scheduled into 45 timeslots and 21 rooms. The solution to the problem was obtained with minimal computing effort and processing time. This study showed that modelling and remodelling could be carried out easily through a proposed parameterised model formulation. The proposed approach has also successfully maximised room utilisation and minimised the number of timeslots required to deliver all the lectures. This finding may facilitate the widespread implementation of automated timetabling systems to larger scale problems and a wider variety of application domains.     

A fuzzy inexact two-phase programming approach to solving optimal allocation problems in water resources management

Inappropriate agricultural activities are the main reasons of water shortage and environmental pollution in many rural areas. How to generate preferred decision schemes for agricultural activities is a critical issue for decision makers. In this study, a two-phase programming approach is advanced for regional water resources allocation in a rural region of China. The approach shows applicability when the uncertain inputs are provided as intervals and such uncertainty is desired to be delivered to the corresponding solutions. Multiple control variables are introduced both in the objective function and constraints of the programming model, which make it possible for the constraints being relaxed under respective levels. A more satisfactory objective value can thus be expected as well as the impact of each constraint on the modeling outputs can be clarified effectively. The decision variables are useful for decision makers to justify and/or adjust the decision schemes for agricultural activities through incorporation of their implicit knowledge on water allocation management.     

A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management

This paper presents a multi-level Taguchi-factorial two-stage stochastic programming (MTTSP) approach for supporting water resources management under parameter uncertainties and their interactions. MTTSP is capable of performing uncertainty analysis, policy analysis, factor screening, and interaction detection in a comprehensive and systematic way. A water resources management problem is used to demonstrate the applicability of the proposed approach. The results indicate that interval solutions can be generated for the objective function and decision variables, and a variety of decision alternatives can be obtained under different policy scenarios. The experimental data obtained from the Taguchi’s orthogonal array design are helpful in identifying the significant factors affecting the total net benefit. Then the findings from the multi-level factorial experiment reveal the latent interactions among those important factors and their curvature effects on the model response. Such a sequential strategy of experimental designs is useful in analyzing the interactions for a large number of factors in a computationally efficient manner.     

Wireless network capacity management: A real options approach

This paper applies financial option valuation methods to new wireless network capacity investment decision timing. In particular, we consider the case of network capacity for cellular telephone service. Given a cluster of base stations (with a certain traffic capacity per base station), we determine when it is optimal to increase capacity for each of the base stations contained in the cluster. We express this in terms of the fraction of total cluster capacity in use, i.e. we calculate the optimal time to upgrade in terms of the ratio of observed usage to existing capacity. We study the optimal decision problem of adding new capacity in the presence of stochastic wireless demand for services. A four factor algorithm is developed, based on a real options formulation. Numerical examples are provided to illustrate various aspects of the model.     

Continuous iterations of dynamical maps: An axiomatic approach

In this paper, an axiomatic definition of continuous iterations of a dynamical map is provided. From the axioms that define common properties of all continuous iterations, it will be demonstrated that continuous iterations that are also derivable must satisfy a certain nonlinear differential equation, herein referred as the “Equation of Derivable Continuous Iterations”. A general solution of this equation will be obtained by means of the Laplace transform and it will be shown that derivable continuous iterations of a map must have a certain functional form. A formula for analytically calculating derivable continuous iterations of maps with at least a fixed point is provided.     

Stabilizing management of fluctuating resources

We consider a resource management problem in which the management objective is to minimize fluctuations in resource stocks. Stabilizing management policies constitute the designing of memoryless state feedback control strategies for a discrete time resource model which contains unknown but bounded fluctuations. We also show that the problem of maximizing sustainable yield in an uncertain fishery can be considered as the problem of stabilizing of the stock level.The paper corresponds to an invited talk at the 14th Symposium on Operations Research, Ulm, September 6–8, 1989.The support by Yrjö Jahnsson Foundation is gratefully acknowledged.This work was supported by NSF and AFOSR under grant ECS 8602524.     

Fuzzy goal programming for inventory management: A bacterial foraging approach

An efficient inventory planning approach in today’s global trading regime is necessary not only for increasing the profit margin, but also to maintain system flexibility for achieving higher customer satisfaction. Such an approach should hence be comprised of a prudent inventory policy and clear satisfaction of stakeholder’s goals. Relative significance given to various objectives in a supply chain network varies with product as well as time. In this paper, a model is proposed to fill this void for a single product inventory control of a supply chain consisting of three echelons. A generic modification proposed to the membership functions of the fuzzy goal-programming approach is used to mathematically map the aspiration levels of the decision maker. The bacterial foraging algorithm has been modified with enhancement of the algorithms’ capability to map integer solution spaces and utilised to solve resulting fuzzy multi-objective function. An illustrative example comprehensively covers various decision scenarios and highlights the underlying managerial insights.     

Corporate valuation,capital structure and risk management: A stochastic DCF approach

In this article we discuss a general stochastic framework for designing corporate investment, financing and risk management strategies for financially constrained firms. The strategy entailing the highest benefits for shareholders is considered to be the optimal strategy. This paper focuses on a simulation of present value distributions of the capital positions of a company, explicitly taking into account the risk of fluctuations in future cash flow as well as the risk of insolvency. The present value distribution of equity is used as a central instrument for evaluation of shareholder benefits. Expected present values are also computed. The investment and financing policy of the company pursued at the time of the valuation is reflected in certain global model parameters, which themselves influence the future profit distribution policy of the company. The main parameters are the extent of debt, the annual debt funding requirements, the average earnings power of the company – expressed as an expected annual return on total capital – and the risk of annual earnings – expressed as the standard deviation of the annual return on total capital. An explicit illustration of the volatility risk and default risk seems not only to be a suitable way of illustrating the impact of capital structure on corporate value. Such an depiction may also provide answers to the question of the link between hedging and enterprise value. This paper highlights the fact that investment, finance and hedging strategies should go hand in hand.     

Multi-criteria analysis and the resolution of sustainable development dilemmas: A stakeholder management approach

We demonstrate that stakeholder-oriented multi-criteria analysis (MCA) can adequately address a variety of sustainable development dilemmas in decision-making, especially when applied to complex project evaluations involving multiple objectives and multiple stakeholder groups. Such evaluations are typically geared towards satisfying simultaneously private economic goals, broader social objectives and environmental targets. We show that, under specific conditions, a variety of stakeholder-oriented MCA approaches may be able to contribute substantively to the resolution or improved governance of societal conflicts and the pursuit of the public good in the form of sustainable development. We contrast the potential usefulness of these stakeholder-oriented approaches – in terms of their ability to contribute to sustainable development – with more conventional MCA approaches and social cost–benefit analysis.     

A receding horizon control approach for integrated vector management of Aedes aegypti using chemical and biological control: A mono and a multiobjective approach

This paper addresses an integrated vector management (IVM) approach for combating Aedes aegypti, the transmission vector of dengue, zika, and chikungunya diseases, some of the most important viral epidemics worldwide. In order to tackle this problem, a receding horizon control (RHC) strategy is adopted, considering a mono-objective and a multiobjective version of the optimal control model of combating the mosquito using chemical and biological control. RHC is essentially a suboptimal scheme of classical optimal control strategies considering discrete-time approximations. The integrated vector control actions used in this work consist in applying insecticides and inserting sterile males produced by irradiation in the population of mosquitoes. The cost function is defined in terms of social and economic costs, in order to quantify the effectiveness of the proposed epidemiological control throughout a time window of 4 months. Numerical simulations show that the obtained results are better than those from the optimal control strategies found in literature. Furthermore, through the application of the multiobjetive approach, varying the scenarios in the mono-objective formulation is no longer necessary and a set of optimal strategies can be obtained at once. Finally, in order to help health authorities in the choice of the best solution of the Pareto-optimal set to be implemented in practice, a cost-effectiveness analysis is performed and a strategy representing the most cost-effective control policy is obtained.     

A 4D-sequencing approach for air traffic management

The current air traffic system is forecasted to face strong challenges due to the continuous increase in air traffic demand. Hence, there is a need for new types of organization permitting a more efficient air traffic management, with both a high capacity and a high level of safety, and possibly with a reduced environmental impact. In this article, we study a holistic approach, consisting in designing across Europe a very organized air traffic system, as opposed to free flight, to reduce costs while maintaining safety.     

Efficiency and total quality management in health care organizations: A dynamic frontier approach

This paper analyses hospital performance using Data Envelopment Analysis (DEA) and the Malmquist productivity index. We follow two approaches to quantify movements in productivity: (1) the traditional approach that only considers output and input variables; and (2) a more comprehensive approach that incorporates movements in quality and restricts some achievements, if quality is reduced. On the premise that the indicator for quality (nosocomial infections) is equivalent to a bad output, we explore the characteristics of, and compare the results of, the different technological ways to incorporate quality (good or bad attributes, strong or weak disposability technological assumptions). After discussing the virtues and limitations of the existing possibilities, the paper presents a better formulation that allows the preservation of TQM postulates. The decomposition in the Malmquist productivity index shows an improvement in productivity and a positive technical change, especially when quality is introduced. This paper forms part of a more extensive research work, financed by the Spanish Science and Technology Ministry (ref. SEC2003-047707).     

A stackelberg game approach to distributed spectrum management

We consider a cognitive radio system with one primary (licensed) user and multiple secondary (unlicensed) users. Given the interference temperature constraint, the secondary users compete for the available spectrum to fulfill their own communication need. Borrowing the concept of price from market theory, we develop a decentralized Stackelberg game formulation for power allocation. In this scheme, the primary user (leader) announces prices for the available tones such that a system utility is maximized. Using the announced prices, secondary users (followers) compete for the available bandwidth to maximize their own utilities. We show that this Stackelberg game is polynomial time solvable under certain channel conditions. When the individual power constraints of secondary users are inactive (due to strict interference temperature constraint), the proposed distributed power control method is decomposable across the tones and unlike normal water-filling it respects the interference temperature constraints of the primary user. When individual power constraints are active, we propose a distributed approach that solves the problem under an aggregate interference temperature constraint. Moreover, we propose a dual decomposition based power control method and show that it solves the Stackelberg game asymptotically when the number of tones becomes large.     

Mixture densities for project management activity times: A robust approach to PERT

PERT is a widely utilized framework for project management. However, as a result of underlying assumptions about the activity times, the PERT formulas prescribe a light-tailed distribution with a constant variance conditional on the range. Given the pervasiveness of heavy-tailed phenomena in business contexts as well as inherently differing levels of uncertainty about different activities, there is a need for a more flexible distribution which allows for varying amounts of dispersion and greater likelihoods of more extreme tail-area events. In particular, we argue that the tail-area decay of an activity time distribution is a key factor which has been insufficiently considered previously. We provide a distribution which permits varying amounts of dispersion and greater likelihoods of more extreme tail-area events that is straightforward to implement with expert judgments. Moreover, the distribution can be integrated into the PERT framework such that the classic PERT results represent an important special case of the method presented here.     

A stochastic programming approach to cash management in banking

The treasurer of a bank is responsible for the cash management of several banking activities. In this work, we focus on two of them: cash management in automatic teller machines (ATMs), and in the compensation of credit card transactions. In both cases a decision must be taken according to a future customers demand, which is uncertain. From historical data we can obtain a discrete probability distribution of this demand, which allows the application of stochastic programming techniques. We present stochastic programming models for each problem. Two short-term and one mid-term models are presented for ATMs. The short-term model with fixed costs results in an integer problem which is solved by a fast (i.e. linear running time) algorithm. The short-term model with fixed and staircase costs is solved through its MILP equivalent deterministic formulation. The mid-term model with fixed and staircase costs gives rise to a multi-stage stochastic problem, which is also solved by its MILP deterministic equivalent. The model for compensation of credit card transactions results in a closed form solution. The optimal solutions of those models are the best decisions to be taken by the bank, and provide the basis for a decision support system.     

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence.This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities.The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities.