## 1 Introduction
[6] described the finding that over a wide range of parameter values typically seen in the remanufacturing industry, a grading system increases profit and consequently profit increases as the amount of returns increases. Therefore, sorting and quality grading play major roles in core acquisition for remanufacturing systems when considering the management of uncertain incoming core quality. Sorting operations in core acquisition are vital for two important reasons. First, to identify the physical, usage, and technological conditions of incoming cores, where they are sorted by their quality level before any remanufacturing processes. Second, sorting operations represent an immediate solution to mitigating quality uncertainty in the core acquisition [7; 8; 9]. Sorting problems can be broadly defined as a case where a sets of alternatives are grouped in an ordinal manner according to the absolute evaluation, beginning with those that include the most preferred alternatives to those that include the least preferred alternatives [10]. Quality sorting in a remanufacturing system plays an important role for grading cores according to their different conditions in order to plan the remanufacturing process and the reduce the cost of remanufacturing. Cores with similar quality grades can be remanufactured with dedicated processes such that the time and cost can be handled efficiently. Quality classification and sorting policies are urgent and direct solutions that are used in remanufacturing systems to handle the source variability in incoming products [8]. Unfortunately, a lack of information from end users can lead to inaccuracy in the quality sorting process. Complete information is needed in order to determine the quality levels of incoming cores. Moreover, when cores are sorted into different quality grades, limited quality data makes it difficult to estimate the associated quality level and the process planning stage thus becomes difficult. To manage quality uncertainty issues, the quality control of incoming cores has become an important strategy for remanufacturing companies. The term quality control is used here to refer to the part of core acquisition management focused on fulfilling quality requirements for incoming cores. Recent evidence suggests that fast sorting in long-term quality control can be accomplished by installing information and communication technology, e.g., automatic sorting systems using radio frequency identification (RFID) or semi-automatic, sensors, bar codes, and other technologies to automate product monitoring and testing in order to acquire valuable usage data to assess remanufacturing feasibility [5; 10; 11]. For instance, in order to record operating hours and speed, Bosch integrated chips into electric motor power tools [12]. Afterward, they evaluated tool quality and sorted into two classes, either remanufacturable or non-remanufacturable. Unfortunately, these methods do not always guarantee usefulness for many remanufacturers. These technologies are only useful for original equipment remanufacturers (OER) who have control over the product design and wish to use such practice to invest in long-term payback if it is economically feasible. These methods are an impractical option for independent or contract remanufacturers. Alternative approaches are necessary to solve the problem of uncertain quality for remanufacturing with short-term quality control. Quality sorting is used to directly control and categorize incoming cores into several quality classes, from the most preferred class to the less preferred class to justify the economic and technical viability for remanufacturing. One can expect that cores with a similar quality class will need similar re-processing operations. In this context, quality uncertainty refers to the required information to be used to assess which conditions of the incoming core are not precisely known. Several methods currently exist to deal with uncertainty.