Applications of Management Science: Volume 18

In this chapter, a case of reverse supply chain is considered, where a product recovery facility receives sensors and Radio Frequency Identification (RFID) tags embedded End-Of-Life (EOL) products. Sensors and RFID tags can capture and store component’s life cycle information during its economic life. This technology can provide data about contents and conditions of products and components without the need of actual disassembly and inspection. It also determines the remaining lives of the components which eventually translate into their quality levels.

The example considered here presents an advanced-repair-to-order-and-disassembly-to-order system. It disassembles the components to meet the components’ demands, repairs the products to meet the products’ demands and recycles the materials to meet the materials’ demands. The received EOL products may have different design alternatives. The objective of the proposed multi-criteria decision-making model is to determine which of the design alternatives is best in fulfilling the various criteria.

The purpose of this chapter is to solve multi-objective formulation for traveling salesman and transportation problems. Computations are based on real data for the road freight transportation of a Spanish company. The company was selected because of its importance in Spanish economy and market. This company is important in the whole country; however, it has its higher importance in the northern part of Spain. The requirements for these models are the minimization of total distance and the CO₂ emissions. To achieve this, it is required to know and carry out the minimization of the total distance traveled by the trucks during the deliveries. The deliveries are going to be executed between the different locations, nodes, in the region, and Elorrio, where the depot is situated. The data have been used to decide the best route in order to obtain a minimization of cost for the company. As it was mentioned earlier, the problems are focused on the reduction of the amount of CO₂ emissions and minimization of total distance; by studying different parameters, the best solutions of route transportation have been obtained. The software used to solve these models is CPLEX solver with AMPL programming language.

The purpose of this chapter is to optimize multi-criteria formulation for green vehicle routing problems by mixed integer programming. This research is about the road freight transportation of a Spanish company of groceries. This company has more power in the north of Spain and hence it was founded there. The data used for the computational experiments are focused in the northern region of Spain. The data have been used to decide the best route in order to obtain a minimization of costs for the company. The problem focused on the distance traveled and the altitude difference; by studying these parameters, the best solution of route transportation has been made. The software used to solve this model is CPLEX solver with AMPL programming language. This has been helpful to obtain the results for the research and some conclusions have been obtained from them.

In order to accomplish the goals of maintaining an effective supply chain, the firm needs to establish and maintain long-term relationships with its suppliers. Most supply chain problems inherently involve multiple conflicting criteria. Risks in the supply chain are dynamic in nature. While some risks can be either reduced or eliminated, new ones will appear.

This chapter will focus on the development of a mufti-criteria model using meta-goal programming to develop a supplier selection process. The goals of the model include (1) the minimization of the net cost for all items, (2) the minimization of the defective items, and (3) the minimization of late-delivered items.

The economic crisis of 2007–2009 had a major negative impact on financial institutions in general. Health and life insurance industry continues to face growth challenges even six years after the economic crisis. Due to the challenges faced by health and life insurance industry, several companies in this industry have merged and some decided to get out of this business altogether. This study benchmarks 10 life and health insurance companies on the basis of return on equity, investment yield, and loss ratio for the year 2009 and 2014.

Processes, in practice, may involve more than one quality characteristic that are of interest. It is quite possible for such quality characteristics to not be independent of each other since the magnitude of one of the characteristics may influence the magnitude of the other characteristics. Under this setting, it is of interest to determine the optimal settings of the process parameters (usually the process mean and the process standard deviation of each quality characteristic) under various objectives. Some of the objectives may be conflicting to each other. In general, it may be possible for the decision-maker to prioritize the objectives. Using such a prioritized scheme, it is of interest to determine the optimal settings of the process mean and standard deviation for each quality characteristic that is being monitored. Such solutions could be labeled as “satisficing” solutions. Sensitivity analyses of the decision variables to the chosen objectives and parameter values are also investigated.

Folding cartons are used in myriad consumer products. For some products, such as hair dye kits, a very high-resolution printing is required. This is typically done using a technology known as Gravure printing. Gravure printing utilizes engraved cylinders which are very expensive. As a result, the printer often combines multiple products on one set of cylinders to minimize the total number of cylinders used. Since the demand between products varies, this can result in overproduction of the low demand products. This chapter presents an integer programming formulation that assigns products across multiple sets of cylinders in order to minimize this overproduction. Sample problems, their solutions and solution times are presented.

US Navy warships are capital-intensive national defense assets that require periodic depot and intermediate level maintenance availabilities (periods). Oftentimes, ship maintenance is deferred or forgone altogether due to geopolitical strife or fiscal challenges. The impacts of missed maintenance are not only a burden on ships’ crews, but they also have a deleterious effect on current and future readiness. It is a difficult task to strike a balance between current and future readiness when insufficient resources are available to sustain a fleet of warships. This paper draws from multi-attribute utility theory (MAUT) to develop a ship maintenance decision-making model that considers attributes from the current and life cycle readiness cohorts. Using the current maintenance plans for two DDG 51-class ships entering availabilities in same fiscal year, this model determines which ship is more capable of absorbing a loss of maintenance and planned modernizations relative to the context of the decision environment. Five attributes are considered for the overall decision: mandatory maintenance, non-mandatory maintenance, mission impact from maintenance, mission impact from planned modernizations, and maintenance backlog. The model presented here is generalizable to a number of U.S. Navy ships and watercraft and can be used to inform decision-makers of the short- and long-term impacts of deferring critical maintenance.

In this chapter, we investigate whether the option contract can coordinate a supply chain when supply chain members have fairness concerns. Specifically, we consider a supply chain consisting of a manufacturer and a retailer where the two members can be either rational or fair-minded, and explore the condition under which the supply chain can be coordinated using an option contract. We follow the traditional newsvendor model by assuming that the market demand is stochastic with a cumulative distribution function and the retail price is exogenous. Under the option contract, the manufacturer’s decision variables include its option price and its exercise price, and the retailer is to decide its order quantity. We derive the equilibrium results for four different scenarios, that is, (i) both the two members are rational, (ii) the supplier is rational but the retailer is fair-minded, (iii) the supplier is fair-minded but the retailer is rational, and (iv) both are fair-minded. While the option contract can coordinate the supply chain when either of the two members is rational, we also find that when both the two members are rational, the option contract can coordinate the supply chain only under some specific conditions. Furthermore, we investigate whether the two members will suffer the disadvantageous or the advantageous inequality in the equilibrium and find some interesting findings.