Industrial Management Engineering

SIMAIR is a C++ based research tool meant for the simulation of airline operations. It provides a means for devising and evaluating various airline recovery mechanisms to handle disruptions, and can also be used as a tool to evaluate the performance of a given schedule of operations. The performance of a given recovery mechanism can be quantified for research and evaluation purposes.

This paper presents the development and the application of simulation models for air cargo terminal operations. As air cargo volume is fast increasing in recent years, air cargo terminals which handle cargos for carriers face challenges to streamline their operations. Air cargo terminals employ diverse storage media and are also equipped with various material handling equipments. Due to the complex and stochastic nature of terminal operations, which makes formulation of analytical model difficult, in this study, simulation models are developed to analyze the air cargo terminal operations. We first employ timed CPN (Colour Petri nets) to model the terminal operations, and then the corresponding simulation model will be developed. In order to validate this simulation model, we run the model based on actual cargo retrieval schedules obtained from an air cargo terminal. The results show that this model provides a good estimate of the terminal performance. The model is then employed to analyze the performance of the airline assignment policy for the objective of minimizing the cargo processing times, and the results show that the proposed policy significantly improves the operational performance of air cargo terminals. Second, the simulation model is employed to analyze the performance of an AS/ RS (Automated Storage and Retrieval System), and the performance of the proposed storage policy is compared with that of the current policy. The simulation experiment also validates the optimal parameter value from the analytic model. The developed models simulate air cargo terminal operations effectively and efficiently, and will aid future studies in the design and control of terminal operations.

Traditional methods of developing flight schedules generally do not take into consideration disruptions that may arise during actual operations. Potential irregularities in airline operations such as equipment failure are not adequately considered during the planning stage of a flight schedule. As such, flight schedules cannot be met as planned and their performance is compromised, which may eventually lead to huge losses in revenue for airlines. In this paper, we seek to improve the robustness of a flight schedule by re-timing its departure times. The problem is modeled as a multi-objective optimization problem, and a multi-objective genetic algorithm (MOGA) is developed to solve the problem. To evaluate flight schedules, SIMAIR 2.0, a simulation model which simulates airline operations under operational irregularities, has been employed. The simulation results indicate that we are able to develop schedules with better operation costs and on-time performance through the application of MOGA.

... Roussos (2006) addressed the SCM standard in ubiquitous commerce. ... Centinkaya and Lee (2002) present an optimization model for coordinating inventory and trans-portation decisions at ... The optimal hybrid dispatch policy with stochastic demand is studied by Ching and Tai ...

ABSTRACT We consider an inventory model for perishable products with stock-dependent demand under inflation. It is assumed that the supplier offers a credit period to the retailer, and the length of credit period is dependent on the order quantity. The retailer does not need to pay the purchasing cost until the end of credit period. If the revenue earned by the end of credit period is enough to pay the purchasing cost or there is budget, the balance is settled and the supplier does not charge any interest. Otherwise, the supplier charges interest for unpaid balance after credit period, and the interest and the remaining payments are made at the end of the replenishment cycle. The objective is to minimize the retailer’s (net) present value of cost. We show that there is an optimal cycle length to minimize the present value of cost; furthermore, a solution procedure is given to find the optimal solution. Numerical experiments are provided to illustrate the proposed model.

This study investigates the impacts of an electronic marketplace with multiple independent retailers for a smart grocery ordering system. Apart from replenishing products from suppliers, the system can also purchase/sell products from/to the electronic marketplace through ‘spot shops’. Both static and dynamic pricing models for the electronic marketplace are developed. An extensive numerical experiment is conducted and the results show

SIMAIR is a C++ based research tool meant for the simulation of airline operations. It provides a means for devising and evaluating various airline recovery mechanisms to handle disruptions, and can also be used as a tool to evaluate the performance of a given schedule of operations. The performance of a given recovery mechanism can be quantified for research and evaluation purposes.

Photonic Network Communications, 6:2, 151±160, 2003 © 2003 Kluwer Academic Publishers. Manufactured in The Netherlands. ... A Location-Routing Problem in Designing Optical Internet Access with ... Youngho Lee*, Seong-in Kim Department of Industrial Systems ...

This paper is concerned with the rectilinear distance location-allocation problem (RDLAP), which seeks the location of capacitated facilities, along with the allocation of their products to customers, so as to minimize total costs that are proportional to rectilinear distances and the amount shipped. Using a localization result, we present a new formulation of this problem as a mixed-integer bilinear programming problem. The problem is then reformulated using a reformulation linearization technique (RLT) as a linear mixed-integer problem that is shown to possess a tight linear programming relaxation. A branch-and-bound algorithm is then designed to implicitly enumerate over the location decision variable space. The special structure of the underlying linear programming relaxation is exploited to derive quick lower bounds via a suitable Lagrangian dual formulation. This methodology enables us to solve larger problem than heretofore solvable, and affords provably good quality heuristic solutions upon premature termination.

The purification process removes impurity in the solution through a chemical reaction with an additive. The amount of additive to be fed into the process depends on the estimate of its efficiency in removing the impurity. We propose the Box-Jenkins method in time series models for the estimation of efficiency. Through simulation, the performance and the robustness of the method are analyzed under various situations including an actual case and compared with those of existing regression and adaptive methods. The case study determines the amount of zinc dust additive that reacts with copper impurity in a hydrometallurgical zinc purification process. In this study, the Box-Jenkins method has been found superior, in both performance and robustness, to the other existing methods.

In this article, we consider a situation in which a group of facilities need to be constructed in order to serve a given set of customers. However, the facilities cannot guarantee an absolute coverage to any of the customers. Hence, we formulate this problem as one of maximizing the total service reliability of the system subject to a budgetary constraint. For this problem, we develop and test suitable branch-and-bound algorithms and study the effect of problem parameters on solution difficulty. Some generalizations of this problem are also mentioned as possible extensions.

In this paper, we deal with a network design problem arising from the deployment of synchronous optical networks (SONET), a standard of transmission using optical fiber technology. The problem is to find an optimal clustering of traffic demands in the network such that the total number of node assignments (and, hence, add-drop multiplexer equipment requirements) is minimized, while satisfying the ring capacity and node cardinality constraints. This problem can be conceptualized as an edge-capacitated graph partitioning problem with node cardinality constraints. We formulate the problem as a mixed-integer programming model and develop a new branch-and-cut algorithm along with preprocessing routines for optimally solving the problem. We also prescribe an effective heuristic procedure. Promising computational results are obtained using the proposed method.

This paper presents a genetic algorithm to solve the asymmetric traveling salesman problem. The genetic algorithm proposed in this study extends search space by purposefully generating andinclud ing infeasible solutions in the population. Insteadof trying to maintain feasibility with crossover operations, it searches through both feasible andinfeasible regions for goodquality solutions. It is also shown in the article that

Scope and Pnrpoae-In this paper, we examine four problems for finding optimal paths of a single moving service facility which continuously examines the service of existing facilities distributed over a network. Examples might include the case of emergency or patrol cars travelling on a road network from an origin to a destination point along a simple (no loops) path, while maintaining a surveillance of various existing facilities or regions for possible service response. At any given instance of time, a measure of cost with respect to each existing facility is given by the weighted distance separating it from the moving facility, where the weight reflects the relative frequency with which service calls originate from that existing facility, and where the cost of service is proportional to the distance that the facility would need to travel from its current location on its path in order to respond to the particular service call. When the existing facilities are distributed only at the nodes of the network, we seek a path that minimizes the sum of the weighted distances between the service facility and the existing ones over all instants of time during the travel period, and also a path that minimizes the sum of the farthest weighted distances between them over all instants of time during the travel period. The methodology for these two cases is also extended to the problem where the existing facilities are distributed continuously along the links as well as discretely on the nodes of the network. These problems are solved by appropriately redefining link lengths and using a shortest-path algorithm. To ensure adequate coverage of the network, it is also conceivable that the route of a patrol car may be composed of the solutions to a sequence of such problems solved over a series of consecutive designated origin-destination points in the network. Possible extensions of this work include the case of multiple service facilities, and the treatment of congestion related effects on travel over the road network.

As an attempt to facilitate uniform sentencing in the criminal justice system of the Korean Judiciary, we have developed an expert system which determines sentences for trafc (vehicular) offenses described in chapter 268 of the Korean Criminal Code. Through interviews and discussions with judges, we have selected the main factors based upon which respective sentence is determined. Next, on that ground we have established key facts of each main factor, and then have embodied the reasoning process in imposing a sentence. In addition to judges, professional knowledge and experience of medical doctors, pofice officers, and insurance experts are reflected in this system. The expert system developed is a kind of factor comparison model and normative model.

The problem of determining an optimal path of a moving vehicle, considered in , is studied in this paper. We generalize their model by including a general cost structure in the problem and show that a specific, non-trivial cost function in this setting yields an easy solution. This follows from the observation that the variational problem that arises in the model with this particular cost function is the problem of geodesics on the Liouville surface. Through a comparative computational study, we also show that the optimal path for the model with this cost function better approximates the optimal path for the original model in Sherali and Kim than their second-order approximation approach does.