Hakan Yildiz

Supply chain risk management: a literature review

Risk management plays a vital role in effectively operating supply chains in the presence of a variety of uncertainties. Over the years, many researchers have focused on supply chain risk management (SCRM) by contributing in the areas of defining, operationalising and mitigating risks. In this paper, we review and synthesise the extant literature in SCRM in the past decade in a comprehensive manner. The purpose of this paper is threefold. First, we present and categorise SCRM research appearing between 2003 and 2013. Second, we undertake a detailed review associated with research developments in supply chain risk definitions, risk types, risk factors and risk management/mitigation strategies. Third, we analyse the SCRM literature in exploring potential gaps.

Scheduling Major League Baseball Umpires and the Traveling Umpire Problem

The scheduling needs of umpires and referees differ from the needs of sports teams. In some sports leagues, such as Major League Baseball in the United States, umpires travel throughout the leagues territory; they do not have a “home base.” For such leagues, balancing the need to minimize umpire travel and the objective that an umpire should not handle the games of a particular team too frequently is important. We have used our approach, which is based on network optimization and simulated annealing, to successfully schedule Major League Baseball umpires. To develop this approach, we created the traveling umpire problem, which includes the major umpire scheduling issues and also provides a test bed for alternative techniques.

Integrated optimization of customer and supplier logistics at Robert Bosch LLC

Large automotive supply chains typically involve manufacturers pulling materials from their suppliers along the chain, usually by using round-trip truckload routes. The return trips on these routes are used to return empty containers back to the suppliers. The mismatch between the amount of materials and empty containers results in underutilization of the return trips. A supplier can utilize this unused capacity by identifying a subset of promising customer routes that can be combined with its existing supplier routes to save overall costs of the system. Such an integration also leads to other supply chain coordination benefits such as the potential of using crossdocks, more frequent milkruns and ensuing reductions in inventories. We undertake such an integrated study of the inbound logistics from suppliers and the outbound logistics to customers at Robert Bosch LLC, a leading automotive parts manufacturer. We identify the opportunity for significant cost savings by using a mixed-integer programming model that matches opposite flows from and to the customers and suppliers. We consider the problem from a supply chain coordination perspective, where Bosch makes all the transportation arrangements for its customers and suppliers based on the centralized optimum solution, and outline its additional benefits.

Reliable Supply Chain Network Design

Risk management in supply chains has been receiving increased attention in the past few years. In this article, we present formulations for the strategic supply chain network design problem with dual objectives, which usually conflict with each other: minimizing cost and maximizing reliability. Quantifying the total reliability of a network design is not as straightforward as total cost calculation. We use reliability indices and develop analytical formulations that model the impact of upstream supply chain on individual entities’ reliability to quantify the total reliability of a network. The resulting multiobjective nonlinear model is solved using a novel hybrid algorithm that utilizes a genetic algorithm for network design and linear programming for network flow optimization. We demonstrate the application of our approach through illustrative examples in establishing tradeoffs between cost and reliability in network design and present managerial implications.

Bender's Cuts Guided Large Neighborhood Search for the Traveling Umpire Problem

This paper introduces the use of Benders Cuts to guide a Large Neighborhood Search to solve the Traveling Umpire Problem, a sports scheduling problem inspired by the real-life needs of the officials of a sports league. At each time slot, a Greedy Matching heuristic is used to construct a schedule. When an infeasibility is recognized Benders cuts are generated, which guides a Large Neighborhood Search to ensure feasibility and to improve the solution.

Locally Optimized Crossover for the Traveling Umpire Problem

This paper presents a genetic algorithm (GA) to solve the Traveling Umpire Problem, which is a recently introduced sports scheduling problem that is based on the most important features of the real Major League Baseball umpire scheduling problem. In our GA, contrary to the traditional way of randomly obtaining new solutions from parent solutions, we obtain partially optimized solutions with a Locally Optimized Crossover operator. This operator also presents a link between the evolutionary mechanism on a population of solutions and the local search on a single solution. We present improved results over other methods on benchmark instances.

Planning for Meals-on-Wheels: Algorithms and Application

Home-delivered meals provision, also known as meals-on-wheels, is a volunteer-staffed activity for which little strategic planning is performed. We develop a Memetic Algorithm to solve the Home Delivered Meals Location-Routing Problem. This planning model addresses facility location, allocation of demand to facilities, and design of delivery routes, while balancing efficiency and effectiveness considerations. The case study presented on a large data set shows how trade-off curves, which are very useful for decision making, can be obtained by the method developed.

Models for supplier selection and risk mitigation: a holistic approach

According to a study conducted by PwC and the Business Continuity Institute in 2013, 75% of companies experience at least one major supply chain disruption a year and majority of the disruptions were caused by supply-related problems. With an increasing emphasis on upstream risk, risk management in supplier selection has become a critical issue faced by companies. Although previous studies proposed different methods and tools for effective and efficient supplier selection, only few approaches have attempted to incorporate risk mitigation strategies in supplier selection decisions. Our study aims to fill this gap by considering a wide range of quantitative and qualitative risk factors in supplier selection and evaluates the efficacy of alternative risk mitigation strategies in this context. Moreover, we suggest that both upstream and downstream strategies should be utilised simultaneously rather than relying on a single type of strategy. We further suggest that it is critical to align upstream and downstream risk mitigation strategies to reduce risk. We employ multi-objective optimization-based simulation in developing a decision model and consider data from an automotive parts manufacturer to demonstrate the application of our approach.

A comprehensive annual delivery program for upstream liquefied natural gas supply chain

Developing a cost-effective annual delivery program (ADP) is a challenging task for liquefied natural gas (LNG) suppliers, especially for LNG supply chains with large number of vessels and customers. Given significant operational costs in LNG delivery operations, cost-effective ADPs can yield substantial savings, adding up to millions. Providing an extensive account of supply chain operations and contractual terms, this paper aims to consider a realistic ADP problem faced by large LNG suppliers; suggest alternative delivery options, such as split-delivery; and propose an efficient heuristic solution which outperforms commercial optimizers. The comprehensive numerical study in this research demonstrates that contrary to the common belief in practice, split-delivery may generate substantial cost reductions in LNG supply chains.