Asia-Pacific Journal of Operational Research

In recent times, sustainability has become more important for businesses. Accordingly, product remanufacturing has emerged as an interesting topic, as it is generally considered as a profitable and environmentally friendly end-of-use management option for several products. While extant literature on remanufacturing has comprehensively studied the topic of outsourcing, it has failed to recognize that retailers also have the flexibility to engage in remanufacturing. However, in recent years, several brand name retailers have established remanufacturing operations. The following question arises: Should original equipment manufacturers (OEMs) outsource their remanufacturing operations to their retailers? To answer this question, two models are developed in which an OEM interacts with an independent retailer on remanufacturing operations with the option to either remanufacture all products in-house (Model M) or outsource remanufacturing to their retailer (Model R). The result shows that although model M potentially facilitates greater economic, social, and environmental sustainability, it has costs for the retailer. Finally, a revenue-sharing contract is proposed to achieve a “win-win-win” outcome that has economic, social, and environmental benefits for all parties.

Logistics delivery companies typically deal with delivery problems that are strictly constrained by time while ensuring optimality of the solution to remain competitive. Often, the companies depend on intuition and experience of the planners and couriers in their daily operations. Therefore, despite the variability-characterizing daily deliveries, the number of vehicles used every day are relatively constant. This motivates us towards reducing the operational variable costs by proposing an efficient heuristic that improves on the clustering and routing phases. In this paper, a decision support system (DSS) and the corresponding clustering and routing methodology are presented, incorporating the driver’s experience, the company’s historical data and Google map’s data. The proposed heuristic performs as well as $k$-means algorithm while having other notable advantages. The superiority of the proposed approach has been illustrated through numerical examples.

The traditional cross-efficiency method has been widely used to evaluate the efficiencies of decision-making units (DMUs) and fully rank DMUs. However, it has several defects, such as excessive weight flexibility, the non-uniqueness of cross-efficiencies, and great self-interest influence on aggregation. To overcome these problems, this paper proposes a new cross-efficiency method embedding weight restrictions and aggregation based on geometric mean. Specifically, two novel weight restriction models (common restrictions on virtual weights model and common restrictions on weights model) are given to overcome the weight flexibility and the non-uniqueness of cross-efficiencies to some extent, and the geometric mean method is applied to aggregate cross-efficiency in order to reduce the self-interest influence. An empirical case is used to illustrate the proposed method.

In this paper, we propose a new method for solving multiple criteria decision-making/aiding (MCDM/A) sorting problems in the context of multi-attribute value theory (MAVT), based on a flexible and interactive elicitation process. It uses partial information to require less information from the decision maker (DM), which is given in the form of preference statements. The proposed method keeps the axiomatic structure of the traditional tradeoff elicitation procedure, without requiring exact values of indifference to be set, which can be a difficult task for the DM to perform. The use of linear programming, combined with the decision rules, allows an alternative to be assigned into a class without the need to provide complete information. By being flexible and interactive, the proposed method allows the DM to monitor the range of possible classes for each alternative at any level of information available during the process, which can save time and effort. The applicability of the method is shown by solving a project management problem on sorting activities.

In this paper, a closed-loop supply chain consisting of a manufacturer, a retailer and a third-party remanufacturer responsible for collecting used products and remanufacturing is constructed. Considering the quality level of remanufactured products, four kinds of closed-loop supply chain alliance structure models are constructed. The optimal equilibrium decisions of these four models are compared and analyzed. The optimal decisions of the models are verified by numerical analysis. Furthermore, the impacts of the quality of remanufactured products and the decision influence of the third-party remanufacturer in the alliance on the remanufacturer’s decision are further analyzed. The results show that remanufactured products are competitive with new products, and the improvement of the remanufactured product quality will reduce the market demand of new products. The equilibrium decision of the closed-loop supply chain is affected by the alliance behavior of members in the closed-loop supply chain and the quality level of remanufactured products. The higher the decision concentration of the closed-loop supply chain is, the more favorable the supply chain is; the higher the remanufacturing quality level is, the more favorable the supply chain is, and the alliance decision of the third-party remanufacturer is affected by the quality level of remanufactured products and the decision-making influence of the third-party remanufacturer in the alliance structure. We find that the improvement of the concentration degree of closed-loop supply chain decision can benefit the supply chain by improving the remanufacturing quality level, which has direct effect on the alliance decision of the third-party remanufacturer. In most cases, the choice of the alliance is the dominant decision of the third-party remanufacturer.

A monopolistic video site provides three commercial modes for viewers: paid, free, and hybrid. In paid mode, the video site provides high-definition video with no advertising (“paid video”), but viewers must pay for watching; in free mode, the video site provides free video with high or standard definition, and viewers have to watch advertisements; in hybrid mode, the video site provides both paid and free video. Our objective is to determine the optimal price, advertising amount, and free video definition to maximize the site’s profits according to viewer characteristics. In doing so, we take into account bandwidth costs, which are correlated with video definition. We study the optimal profit of the video site in different cases and find that in free mode, the video site should provide high-definition free video. Through numerical examples, we find that the system parameters determine whether the optimal profit can be obtained by providing paid, free, or hybrid mode.

In this paper, based on Chen–Harker–Kanzow–Smale smooth function, we obtain a smoothing homotopy method to solve the second-order cone complementarity problem. The global convergence is ensured under certain non-monotonicity condition for the defined mapping $F$. The numerical results illustrate that this method is feasible.

The average transportation cost minimization of capacitated transportation problem with bounds on rim conditions (CTPBRC) is an important optimization problem due to the requirement of low unit cost consumption in production system. In the literature, there is only one approach to solving a special case of this problem, but it is not applicable to the general case. In this paper, this problem is reduced to a series of finding the minimum cost maximum flow in a network with lower and upper arc capacities, and two iterative algorithms are proposed as more generalized solution method for this problem as compared to the existing approach. Computational experiments on randomly generated instances validate that the two iterative algorithms are generally able to find the minimum average transportation cost solution to CTPBRC efficiently for the general case, in which one iterative algorithm has higher efficiency than the other for large size instances.