Sharif H. Melouk

A simulation-optimization approach for integrated sourcing and inventory decisions

In this paper, we study a generalized vendor selection problem that integrates vendor selection and inventory replenishment decisions of a firm. In addition to vendor-specific procurement and management costs, we consider inventory replenishment, holding, and backorder costs explicitly to meet stationary stochastic demand faced by the firm. Our goal is to select the best set of vendors along with the optimum inventory decisions at each plant of the firm so that we minimize the system-wide total costs and achieve desired service and reliability levels. Due to uncertainties inherent in the problem related to demand observed by the firm, quality provided by vendors, and disruptions observed by vendors, we utilize a simulation-optimization approach to solve the problem. More specifically, we build a discrete-event simulation model to evaluate the objective function of the problem that works in concert with a scatter search-based metaheuristic optimization approach to search the solution space. Computational results not only provide managerial insights and measure the significance of intangible factors in the vendor selection process but also highlight the importance of computational tools such as simulation-optimization for the vendor selection problem.

A Simulation Optimization-Based Decision Support Tool for Mitigating Traffic Congestion

Traffic congestion has grown considerably in the United States over the past 20 years. In this paper, we develop a robust decision support tool based on simulation optimization to evaluate and recommend congestion mitigation strategies to transportation system decision-makers. A tabu search-based optimizer determines different network design strategies on the road network while a traffic simulator evaluates the goodness of fit. The tool is tested with real-world traffic data.

Managing Resource Allocation and Task Prioritization Decisions in Large Scale Virtual Collaborative Development Projects

Business rules guide information system development and maintenance in the organization. The issue of business rules for enterprise information systems has recently received considerable attention. However, as yet little research has been reported on a systematic approach to business rules management. This paper proposes a business rules management model. In this model, business rules are supported by three types of independent information system components: system setting, database, and procedural module. A business rule can be formalized into one or more elementary rule, and a formalized elementary rule is associated with one and only one information system component. Business rules, system components, and their interconnected relationships can be organized into an XML enabled repository for the system development, customization, and maintenance. An example of artifact of business rules management system can be found in an apartment rental management system. This example is used to illustrate the concept of business rules management. DOI: 10.4018/irmj.2010102604 IGI PUBLISHING This paper appears in the publication, Resources Management Journal, Volume 23, Issue 1 edited by Mehdi Khosrow-Pour

Parallel-machine scheduling to minimize overtime and waste costs

This article considers scheduling products in a parallel, non-identical machine environment subject to sequence-dependent setup costs and sequence-dependent setup times, where production waste and processing time of a product depend on feasible machine assignments. A Mixed-Integer Programming (MIP) formulation is developed that captures trade-offs between overtime labor costs and waste costs. Two solution procedures are developed to address large problem instances. One procedure is an algorithm that determines a vector of product-to-machine assignments that assists an MIP solver to find an initial feasible solution. The second procedure is a decomposition heuristic that iteratively solves a relaxed subproblem and uses the subproblem solution to fix assignment variables in the main MIP formulation. In addition, bounds on the quality of solutions found using the decomposition heuristic are presented. Experiments are conducted that show the developed formulation outperforms more traditional scheduling objectives with respect to the waste and overtime labor costs. Additional experimentation investigates the effects that problem parameter values have on total waste and labor costs, performance of the approaches, and the use of overtime labor.

A decomposition-based heuristic for stochastic emergency routing problems

Abstract This paper proposes a decomposition-based heuristic for a network delivery problem in which relief workers acquire valuable emergency supplies from relief warehouses, and transport them to meet the urgent needs of distressed population centres. The problem context dictates that the relief items reach these population centres before critical deadlines. However, co-ordination challenges and random disruptions introduce uncertainty in both network travel times and the destination deadlines. Hence, relief workers have to negotiate the tension between ensuring a high probability of punctual delivery and maximising the combined value of the relief supplies delivered. For an arbitrary routing scheme which guarantees punctual delivery in an uncertainty-free state of nature, the heuristic yields an upper bound on the probability that, under uncertainty, the routing scheme described will lead to tardy delivery. We demonstrate our solution approach on a small numerical example and glean insights from experiments on a realistically sized problem. Overall, our central model and proposed solution approach are useful to managers who need to evaluate routing options and devise effective operational delivery plans in humanitarian crisis situations.

Analyzing production modifications of a C-130 engine repair facility using simulation

The LRAFB C-130 engine repair facility is one of the top T-56 engine refurbishing plants in the United States Air Force. Currently, the shop is prevented from testing potential contingencies within their environment due to the rapid nature of their engine repair process. A simulation approach is needed to test various scenarios and determine the maximum capacity the shop can handle in its current configuration. Particularly, the simulation describes the consequences of increasing engine production on the shops personnel and throughput production figures for several policy variations. A detailed verification and validation of the model are shown, establishing the computational efficacy of the model in preparation for the comparative analysis. The model is a starting block for an Air Force wide analysis of C-130 engine rebuilding production needs with an overarching goal of standardization in repair methods and efficient operations.

Stochastic resource allocation using a predictor-based heuristic for optimization via simulation

Some combinatorial stochastic resource allocation problems lack algebraically defined objective functions and hence require optimization via simulation as a mechanism for obtaining good solutions. For this class of problems, we propose a new predictor-based heuristic that uses a distance criterion to perform the solution search. To demonstrate our solution approach, we apply this heuristic to the problem of selecting the proper design configuration of an unmanned aerial system (UAS) fleet so as to maximize mission effectiveness. We compare our approach to black box optimization via simulation approaches (two tabu search-based procedures and a greedy heuristic) and glean both methodological and practical insights.

A multi-period dynamic location planning model for emergency response

We investigate a multi-period ambulance location problem for an emergency medical service (EMS) provider that routinely aims for high quality medical response in a short period of time. However, both quality and timing of service are very costly goals to achieve. In this research, our goal is to minimize the total operational cost of an EMS organization while maintaining acceptable response times for a newly defined EMS network that consists of supply centers, hospitals, responder locations, and incidents. We propose a new dispatch model, a deferred service model, to analyze the daily operations of ambulances that involve dispatch as needed and redeploy periodically. The main premise of this model is, given incident priority levels, incident demand patterns, and EMS provider resources, to decide which incidents to serve immediately and which incidents to defer to following periods while incurring deferral penalty costs. Additionally, high-priority incidents that are not addressed within the required response window incur delay penalty costs. Considering network size, fleet size, incident patterns, and time-dependent parameters as different factors that may influence the solution, we compare the results in terms of service quality, response time, and total cost through extensive experimentation. Experimental results indicate that sending the closest ambulance to an incident site is not always the best choice.

Team assignments and scheduling for the NCAA basketball tournament

The National Collegiate Athletic Association (NCAA) organizes a mens basketball tournament every March to determine the national champion for the current season. In organizing the tournament, the emphasis is typically on selection of the most deserving teams to participate and providing a fair, equitable environment in which to play that result in a true, undisputed champion for the season. However, there are growing concerns of dwindling actual attendance at tournament games and increasing financial burden on the NCAA related to reimbursable team travel expenses. In this paper, we describe the development of an integer program designed to optimize team assignments in the sense of minimizing the distance travelled by teams to game sites and the corresponding travel costs. The goal is to increase tournament accessibility to fans as well as lessen the financial impact to the NCAA while maintaining the integrity of the tournament. We test our model against actual tournament assignments from the past 5 years. Results show consistent and significant cost savings and reductions in distance travelled without compromising the fairness and structure of the tournament. Overall, we demonstrate the usefulness of the model in both operational and strategic business decisions.

Alternative metrics to measure EMS system performance

abstractIn the development of strategy for the response to emergent incidents, emergency medical services (EMS) organizations must properly manage their resources while also adhering to response time mandates established by contractual agreements. Performance of an EMS system is typically measured by focusing on the response time of its first responders. However, given that some incidents require the response of multiple emergency vehicles, investigating only the initial response to incidents is inadequate. In this research, we propose two new metrics, in addition to the first response metric, to evaluate the performance of EMS operations: total response time and last responder response time. We develop three mixed integer programming formulations, each one focused on minimizing one of the three metrics, to model the assignment of emergency vehicles to incidents. We also propose a fourth model that combines the metrics via a weighted objective function. This model allows for the simultaneous consideration of the response metrics when evaluating the effectiveness of an emergency response dispatch policy. Experimental results, from comparisons of the models against a greedy dispatch policy, suggest the consideration of multiple response metrics leads to a more robust and effective dispatch policy. Finally, analysis using the models has potential to shape improved strategic and operational policies of EMS organizations. Journal of the Operational Research Society advance online publication, 29 June 2016; doi:10.1057/jors.2016.39