Journal of the Operational Research Society

Volpato, Neri; Galvão, Lauro Cesar; Nunes, Luiz Fernando; Souza, Rômulo Ianuch; Oguido, Karina

doi: 10.1080/01605682.2019.1590135pmid: N/A

AbstractBuilding time is an important issue in material extrusion additive manufacturing. The extrusion head must stop and jump from one point to another to start a new deposition. The length of the head repositioning can be reduced by applying optimisation during path planning. This work presents two optimisation algorithms, one based on the greedy option and one that combines the heuristics known as the nearest insertion (NI) and the 2-opt. The proposed algorithms are quite simple to implement and the main filling steps in the material deposition process have been mapped and considered in the analysis. The results show that it is possible to reduce considerably the repositioning distance with the proposed methods, and that the NI method usually outperformed the greedy method. It was also observed that the result was affected by the geometry of the part being analysed.

Gartner, Daniel; Padman, Rema

doi: 10.1080/01605682.2019.1590509pmid: N/A

AbstractIn this paper, we build on and extend Gartner and Kolisch (2014)’s hospital-wide patient scheduling problem. Their contribution margin maximising model decides on the patients’ discharge date and therefore the length of stay. Decisions such as the allocation of scarce hospital resources along the clinical pathways are taken. Our extensions which are modeled as a mathematical program include admission decisions and flexible patient-to-specialty assignments to account for multi-morbid patients. Another flexibility extension is that one out of multiple surgical teams can be assigned to each patient. Furthermore, we consider overtime availability of human resources such as residents and nurses. Finally, we include these extensions in the rolling-horizon approach and account for lognormal distributed recovery times and remaining resource capacity for elective patients. Our computational study on real-world instances reveals that, if overtime flexibility is allowed, up to 5% increase in contribution margin can be achieved by reducing length of stay by up to 30%. At the same time, allowing for overtime can reduce waiting times by up to 33%. Our model can be applied in and generalised towards other patient scheduling problems, for example in cancer care where patients may follow defined cancer pathways.

Xu, Chao; Duan, Yongrui; Huo, Jiazhen

doi: 10.1080/01605682.2019.1590510pmid: N/A

AbstractWe analyse a problem involving the joint pricing of a product and associated service, together with the management of inventory under servitisation. For a finite planning horizon, the firm sells both a product and a product-centric service whose market size depends on the past sales of the product. At the beginning of each period, the firm simultaneously decides the price of the product, the price of the service, and the replenishment quantity. We prove that a modified base-stock list-price policy is optimal to this problem. In addition, we find that there is a trade-off between realising current profit from the product and stimulating demand to increase future profit, and that overlooking this trade-off results in overall loss of profit for the firm. Moreover, the optimal policy that takes the trade-off into account leads to a lower optimal product price compared with a myopic policy, and the optimal price increases as a function of the past sales of the product.

Wang, Jen-Ya

doi: 10.1080/01605682.2019.1590511pmid: N/A

AbstractThe influence of learning effects on job scheduling has been studied for years. By considering learning effects, an operator can schedule jobs in a more precise way and improve on the original schedules. In fact, jobs with duplicate contents (i.e., overlapping jobs) do not require as much processing time as do disjoint jobs. However, this phenomenon is seldom discussed in traditional scheduling models. In this study, a parallel-machine scheduling problem with a learning effect and an overlap effect is introduced. The objective is to minimise the total weighted tardiness of jobs whose processing times are influenced by both effects. A branch-and-bound algorithm comprising a lower bound algorithm is developed to generate the optimal schedules. Compared with past research, two main contributions are made. First, a model considering simultaneously both the learning effect and the overlap effect is proposed. Second, an efficient lower bound algorithm accelerating the execution speed is developed. At the end, computational experiments are conducted to show the execution efficiency and cost effectiveness.

Ishizaka, Alessio; Tasiou, Menelaos; Martínez, Luis

doi: 10.1080/01605682.2019.1595188pmid: N/A

AbstractAnalytic Hierarchy Process (AHP) is a well-founded and popular method in the Multi-Criteria Decision Analysis (MCDA) field. AHPSort, a recently introduced sorting variant, uses crisp class-assignment of alternatives. This can sometimes be misleading, especially for alternatives near the border of two classes. This paper aims at making the class assignment process in AHPSort more flexible by using fuzzy sets theory, which facilitates soft transitions between classes and provides additional information about the membership of alternatives in each class that can be used to fine-tune actions beyond the crisp sorting process. This essentially complements the ordinal information of its crisp variant with cardinal information as to the degree of membership of an alternative to each class. The applicability of the proposed approach is illustrated in a case study that regards the classification of London boroughs according to their safety levels.

Hsieh, Tsu-Pang; Dye, Chung-Yuan; Lai, Kuei Kuei

doi: 10.1080/01605682.2019.1595189pmid: N/A

AbstractThe article formulates a joint dynamic trade credit and advertising problem in which the demand rate varies simultaneously with the length of the credit period offered to the customers and the stock of advertising goodwill depending on the retailer’s current and past advertising efforts. The proposed problem is analysed in the multi-period setting over an infinite horizon in which demand at each period depends on the current and past advertising efforts through the goodwill dynamics. We first show that the retailer would adopt a static credit period strategy, and then demonstrate that the optimal path of the advertising effort is unique and converges monotonically to its corresponding equilibrium over the long run in the opposite direction as the stock of advertising goodwill. Moreover, a set of structural properties is developed to characterise the impacts of model parameters over the optimal decisions. Finally, we offer concluding remarks and suggestions for future studies.

Zandi, Arash; Ramezanian, Reza; Monplaisir, Leslie

doi: 10.1080/01605682.2019.1595190pmid: N/A

AbstractSustainability consciousness in manufacturing has become an interesting topic for many researchers in recent years. There is also more concern in many companies about reducing energy consumption in manufacturing. Improving environmental health and safety, production cost saving, access to governmental incentives such as grants and tax credits and also improving the brand image are the most important reasons which is leading many companies to an environmental-friendly production planning. For example, one of the most applicable scheduling problems deals with planning jobs on numbers of parallel machines. In such an application, different machines have different technologies and different speed and power of energy consumption in manufacturing similar jobs. This article introduced a mathematical formulation which models the green parallel machines scheduling problem with total energy consumption and total completion time as objectives. Due to high computational complexity of the proposed model, a heuristic algorithm is developed to obtain the exact Pareto frontier of these two objectives with a polynomial complexity. Numerical experiments are presented to show the efficiency and speed of the proposed algorithm compared to solving the model using the optimisation software directly.

Lozano, Sebastián; Soltani, Narges

doi: 10.1080/01605682.2019.1599704pmid: N/A

AbstractThe hyperbolic distance function (HDF) reduces all inputs and increases all outputs simultaneously and at the same rate. Although the corresponding data envelopment analysis (DEA) model is non-linear, for constant returns to scale it can be linearised and for variable returns to scale an efficient iterative approach based on the directional distance function (DDF) model can be used. However, HDF does not necessarily project onto an efficient target. To remedy this, lexicographic hyperbolic DEA (LexHDEA) is proposed in this article. Thus, before solving the HDF model, the input or output dimensions that can be improved are determined. A reduced HDF model is then solved, looking for improvements only in these dimensions. If the corresponding target is efficient, then no further steps are necessary. Otherwise, a reduced HDF model that improves only those dimensions that can be further improved is solved. If this improved target is efficient the process stops. Otherwise the process is repeated until eventually the efficient frontier is reached. In addition to guaranteeing an efficient target the proposed approach also computes an efficiency measure that has indication of efficiency and units invariance. The proposed approach can be extended to handle a preference structure, non-discretionary variables and undesirable outputs.

Gan, Guoya; Lee, Hsuan-Shih; Lee, Lynne; Wang, Xianmei; Wang, Qianfeng

doi: 10.1080/01605682.2019.1603792pmid: N/A

AbstractData envelopment analysis (DEA) has been proved to be a powerful approach for measuring the performance of decision making units (DMUs). However, the conventional black-box approach tends to neglect the internal structure of the components and the possibility of having different network structures of DMUs. In reality, DMUs can have complex networks that are in forms of parallel or serial structures and hierarchical processes. For example, in the international shipping industry, the operational tasks can be divided into two stages: supervising the ship dispatch and controlling the work time in the port, which jointly constitute a two-stage operating network structure and each contains its own embedded hierarchical structure. Herein, this study intends to propose a new network hierarchical DEA approach to evaluate the performances of such two-stage structure that embedding the hierarchical structures. Data collected from the Maritime and Port Bureau (MOTC) in Taiwan (2017) is used to validate the reliability and efficiency. The result indicates the effectiveness of the model and provides meaningful implications for the international shipping industry.

Wang, Chong; Chen, Jing; Wang, Lili; Luo, Jiarong

doi: 10.1080/01605682.2019.1599703pmid: N/A

AbstractThis article develops a newsvendor model to examine the optimal pricing and ordering decisions of a supply chain in which the supplier offers both wholesale price and option contracts to a retailer who faces customer returns and uncertain demand. The supplier is the Stackelberg leader who decides the option and exercise prices with a pre-determined wholesale price, and the retailer decides the product order quantity and option order quantity through the supplier’s two contracts. We discuss the impact of customer returns and the option contract on the optimal pricing and ordering decisions, and on the profits of the supplier and the retailer. We show that the retailer’s product order quantity, option order quantity, and expected profit decrease with customer returns rate; the supplier’s optimal option price and exercise price decrease as more customers return products. We also discuss the supply chain coordination mechanism and propose a contract that can achieve supply chain coordination and ensure that both the supplier and the retailer can be more profitable.