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Operations and maintenance management for renewable energy (RE) projects has become increasingly important in improving energy system models' precision. Specifically, some elements are uncertain and difficult to predict, such as temperature conditions or system reliability, and these result in more complicated RE projects. Suitable maintenance and insurance policies are vital to reduce risks for RE system operators. This paper formulates a profit model that integrates system reliability, predictive maintenance, and green insurance into electricity pricing and capacity problems. A non-linear optimization solution procedure is proposed to determine the optimal electricity price, capacity, investment plan, predictive maintenance budget, and insurance level while maximizing company profit. The theoretical results indicate that RE systems' increased reliability decreases the insurance level. However, an increase in the insurance level decreases RE project investments. Therefore, companies can attract more investments for RE projects if RE system reliability increases while insurance costs decrease. Additionally, this work not only presents a numerical analysis with examples and a sensitivity analysis to illustrate the model, but also discusses the opportunities this work offers for managers and analysts in practice. [ABSTRACT FROM AUTHOR]

The Internet provides lower company operating costs, increased product sales, understanding of customer preferences, and closeness to customers. Direct channels break barriers between suppliers and customers and change customer consumption patterns. However, they can also lead to competition and conflicts between upstream and downstream members of the supply chain. This study contributes to supply chain management research by investigating the joint impact of pricing policy, service-level investment, and dual-channel supply chain competition in a duopoly manufacturer channel. By simulating conditions similar to the actual market, the numerical experiment conducted in this study yielded several insights into the management of the dual-channel architecture. A targeted rebate mechanism is used to eliminate channel conflicts and persuade injured parties to accept the introduction of an online channel. [ABSTRACT FROM AUTHOR]

In a microgrid, an efficient energy storage system is necessary to maintain a balance between uncertain supply and demand. Distributed energy storage system (DESS) technology is a good choice for future microgrids. However, it is a challenge in determining the optimal capacity, location, and allocation of storage devices (SDs) for a DESS. This paper proposes a two-stage approach to solve these SD decision-making problems in a microgrid. In the first stage, a continuous approximation approach was used to formulate the SD location, capacity, and renewable energy investment problems from a long-term perspective. In the second stage, the dispatch quantity problems are addressed to minimize the operational cost based on the results of Stage 1. Some examples and real data are used to illustrate the model and solution approaches. The results show that our approach can achieve the cost minimization. The optimal SD location and capacity strategy and the renewable energy investment level are close to the real data obtained from Liu et al. (2018) after 20 runs. • Designing a two-stage approach to solve these SD decision-making problems in a microgrid. • A continuous approximation approach is used to formulate the SD location, capacity, and renewable energy investment problems from a long-term perspective at the first stage. • The dispatch quantity problems are addressed to minimize the operational cost based on the results of Stage 1 at Stage 2. [ABSTRACT FROM AUTHOR]

• Analyze and discuss the company decision-making when banks support to generate renewable energy and demand uncertain. • The repayment ability of the power company depends on sales revenue. • A single newsvendor model is used to determine the optimal renewable energy price, capacity and amount of loan from bank. • Discuss how company responds to the changes of the different situation of energy market. The costs of renewable energy technologies are highly sensitive to financing terms. Power companies are willing to invest in renewable energy generation because of clean and sustainability concerns. However, renewable energy generation poses a potentially high risk, both in generation and consumption. In this study, we consider how a power company makes its decisions if a credit bank willing to lend to it for renewable energy generation. The repayment ability of the company depends on sales revenue under demand uncertainty. We formulate a mathematical model to help the company determine the optimal electricity price, renewable energy capacity, and amount of loan while maximizing the total expected profit. A searching algorithm is proposed to solve the problem. Several numerical examples are provided to illustrate the proposed model and solution approach. Managerially, our study suggests that increasing renewable energy investments through financing institutions requires careful attention to pricing, capacity, and financing policies. [ABSTRACT FROM AUTHOR]

Optimizing the order-fulfillment process is crucial to the logistics industry. Replacing experience-based judgment with intelligent methods in the packing process not only improves work efficiency but also eliminates resource wastage. This study focuses on the three-dimensional multiple bin-size bin packing problem with compatible categories (3D-MBSBPPCC) and different size of the boxes. An algorithm is developed to achieve the best packing pattern while minimizing the number of boxes required and the total unused space in the boxes. In the algorithm, we first use the first-fit decreasing algorithm to find an initial solution. Next, the carton configuration algorithm is applied to perform packing and evaluate the solution. Subsequently, a simulated annealing (SA)-based algorithm is employed to improve the solution by moving the products among the subsets of the solution. Finally, hybrid metaheuristics based on both SA and the genetic algorithm, are proposed to improve the solution quality. We tested the proposed packing algorithms on real-world scenarios. The experimental results demonstrate that the proposed algorithms are effective in solving 3D-MBSBPPCC. [ABSTRACT FROM AUTHOR]

In practice, a vendor may offer a retailer an advance-cash-credit (ACC) payment scheme. This implies the buyer needs to pay a fraction of the purchasing cost before he receives the item (advance payment), some cash when the item is arrived (cash on delivery), and then the remaining purchasing cost after a credit period (credit payment). This paper studies the effect of payment schemes on the supply chain network design. The network consists of an outside supplier, multiple distribution centers (DCs), and multiple retailers. The DCs receive an upstream ACC payment from the supplier. This study attempts to determine the optimal location, allocation, as well as the inventory cycle time while minimizing total cost. A continuous approximation is used in the model development and the time value of money concept is considered, since different payment schemes related to time change the cash value. Numerical studies are adopted to demonstrate the solution approach and the effects of changing parameters on decisions and total cost. This study provides novel management implications for supply chain network designers' reference. The results show that the number of DCs to be opened, the joint replenishment cycle time of DC, and the total cost increase as the interest earned decreases and the interest charged increases. [ABSTRACT FROM AUTHOR]

Given the diversity of styles and sizes in apparel, marker planning which aims to arrange and move all the pattern parts of garments onto a long thin paper before the cutting process is a very important process for the apparel industry. In order to decrease the wastage of fabric after the cutting process, the marker layout essentially needs to be as compact as possible. In this paper, hybrid heuristics are proposed to conduct and achieve an optimized marker layout and length. First, a moving heuristic is presented as a new packing method to arrange and move the patterns without overlapping; here, an initial marker is presented to calculate the length. This heuristic considers multiple rotated angles and flipping positions of the patterns in order to obtain more diverse arrangements. With different arrangements, there is a higher chance of achieving an optimized marker layout and length. To further improve the solution received from the moving heuristic, soft computing algorithms are taken into account, including the genetic algorithm (GA), simulated annealing (SA), and hybrid genetic algorithm-simulated annealing (HGASA) to achieve a shorter length in the marker layout. The best marker length can be obtained from HGASA, which can save almost 28% of the length. Special cases with specific combinations in rotated angles are considered so that the industry can make informed choices on the algorithms suitable to address the marker planning problem. [ABSTRACT FROM AUTHOR]

We explore the supply chain network design problem for a retailer selling perishable products when the supplier provides trade credit and the deterioration rate can be reduced by freshness-keeping effort. Using a continuous approximation model, we derive the total cost of the supply chain, including facility set up and operation cost, ordering cost, freshness keeping cost, transportation cost, inventory-holding cost, and interest cost of trade credit. We prove the convexity of the total cost functions and derive the closed-form solutions of the decision variables, including the service regions of distribution centers, the replenishment cycle time, and the fresh food freshness keeping effort. Finally, we conclude with some managerial insights from the numerical analysis. [ABSTRACT FROM AUTHOR]

We develop an economic production quantity model on the basis of radio frequency identification (RFID) adoption, trade credit, and reworking of imperfect products. We determine the optimal values of production cycle time and RFID investment levels for ordering, just-in-time, and operating efficiencies. On the basis of the relationship between the demand and reworking rates, we classify the model into two cases. Furthermore, on the basis of the relationship between production cycle time and credit period, we divide each case into four subcases. We derive the total manufacturing cost for the subcases and develop an algorithm to solve the four-branch piecewise nonlinear problem. Finally, we illustrate the solution approach and perform numerical analyses to discuss the influences of system parameters on decisions. [ABSTRACT FROM AUTHOR]