Operational Research

Dual-channel supply chain structure, i.e., a traditional retail channel added by an online direct channel, is widely adopted by a lot of firms, including some companies selling deteriorating products (e.g. fruits, vegetables and meats, etc.). However, few papers in literature consider deterioration property of products in dual-channel business models. In this paper, a single-retailer-single-vendor dual-channel supply chain model is studied, in which the vendor sells deteriorating products through its direct online channel and the indirect retail channel. In addition to quantity deterioration, quality of the products also drops with time and affects the demand rate in the retail channel. The pricing decisions and the inventory decisions for the two firms are simultaneously studied. Models of centralized (i.e., the two firms make decisions jointly) and decentralized (i.e., the two firms make decisions separately, vendor as the Stackelberg leader) problems are established. Proper algorithms are proposed to obtain the optimal decisions of prices, ordering frequencies and ordering quantities. The results suggest that decentralization of the supply chain not only erodes the two firms’ profit, but also incurs higher wastes comparing to that under centralization. However, a revenue sharing and two part tariff contract can coordinate the supply chain. Under utilizing the contract, each firm’s profit is improved and the total waste rate of the supply chain is reduced. It is also shown that the contract is more efficient for both firms under higher product deterioration rate. Besides, the contract is more efficient for the retailer, while less efficient for the vendor under higher quality dropping rate. In the model extension, online channel delivery time is assumed to be endogenous and linked to demands in both channels. The results show that products’ deterioration rate and quality dropping rate have significant impacts to the firms’ delivery time decisions, as well as the pricing and inventory decisions.

In this paper we analyze how the way in which the principal’s preferences are visualized may affect the accuracy of representation of this principal by their agent. We study the processes of multi-issue electronic representative negotiations conducted by agents on behalf of their principals by means of the negotiation support system that implements a simple decision support tool for eliciting the preferences and building a system of cardinal ratings for feasible negotiation offers. First, we investigate the accuracy of agents’ scoring systems and compare their concordance to the preferential information provided to them by their principals by means of single verbal description and two different visualization techniques, one using bar graphs and the second—circles (pies). The concordance is measured by means of the notions of ordinal and cardinal accuracy. Then we analyze how the scoring systems with various inaccuracy indexes influence the agents’ perception of negotiation process, i.e. the interpretation of concessions made by parties and the structures of concession paths. We also study what is an impact of inaccurate scoring systems on the negotiation outcomes, i.e. the final contracts, their ratings and efficiency. The results obtained show that the bars are slightly better in more precise representation of principals preferences. They allow agent to determine a little more accurate scoring systems, which help to understand the negotiation process better by minimizing the cardinal error of evaluation of the offers in concession paths. Yet, no significant impact on the outcomes have been found. An interesting prescriptive conclusion that can be drawn is that to assure an adequate representation of principal’s preferences the agents should be offered the bar-based visualization. Also, a checkup mechanism should be introduced to the preference elicitation procedure that assure the agents to be ordinally concordant with the priorities of their principal’s preferences.

In this article we study the situation, where an optimal solution of a combinatorial optimization problem is known and we are equipped with the simple algorithms allowing to adapt our solution to different distortions of the initial data set. We wish to describe the distortions which allow the adaptation of the given optimal solution by the given simple algorithm preserving the optimality of the first. This approach, lying between common stability and reoptimization, is called adaptive stability. In the article we construct the conditions of adaptive stability for a range of combinatorial optimization problems having a particular structure. The obtained conditions allow to build efficiently the corresponding adaptive stability areas. The stability areas may be used for postoptimal preferring among different optimal solutions whether these are multiple solutions belonging to a single mathematical model or a set of optimal solutions corresponding to different models. The abstract concept is illustrated by two examples of combinatorial optimization problems: traveling salesman problem and task distribution problem.

The efficient planning of search and rescue (SAR) operations is highly impactful in the disaster response phase, which offers a limited time window with a declining chance for saving trapped people. The present paper introduces a new robust decision support framework for planning SAR resource deployment in post-disaster districts. A two-stage decomposition approach is applied to formulate the problem as iterative interrelated stages of mixed-integer programming (MIP) models. The first stage presents a robust multi-period allocation model for maximizing fair and effective demand coverage in the affected districts during the entire planning horizon. It takes into account the time-sensitiveness of the operations via a time-dependent demand satisfaction measure and incorporates resource transshipment optimization. The second stage optimizes the routing of the resources allocated in the first stage for each district during the upcoming period. It aims to minimize the weighted sum of SAR demand fulfillment times under consideration of secondary destruction risk, resource collaboration, and rest time requirements. At the end of each period, the proposed framework can be re-executed to capture updated resource, demand, and travel time parameters. To tackle the environment’s inherent uncertainty, an interval-based robust optimization approach is adopted. The proposed framework is solved and analyzed for an urban zone in Iran under an earthquake scenario. Results show that the proposed robust models have superior performance compared to a deterministic approach for adaptation to an uncertain disaster environment. More importantly, they prove to be a strong analysis tool for providing helpful managerial insights for the mitigation and preparedness phases.

Trong các hệ thống sản xuất thực tế, sự xuất hiện của các sản phẩm bị lỗi trong một lô hàng là điều không thể tránh khỏi. Trong khi các sản phẩm này có thể chỉ bị loại bỏ trong ngành thực phẩm, thì trong các ngành công nghệ cao, nơi sản phẩm cuối cùng có giá thành rất cao, chúng có thể được chỉnh sửa với một chi phí nhất định. Một giả định chung trong tài liệu là thời gian kiểm tra cần thiết để xác định các mặt hàng bị lỗi được hoàn thành khi quá trình sản xuất kết thúc. Tuy nhiên, giả định về việc kiểm tra liên tục trong suốt quá trình sản xuất làm phức tạp việc phân tích, khiến nó trở nên bất khả thi cho hầu hết các hệ thống sản xuất, đặc biệt là khi tỷ lệ sản xuất cao và tỷ lệ các mặt hàng bị lỗi thấp, làm cho việc kiểm tra liên tục trong quá trình sản xuất trở nên rất tốn kém. Ngoài ra, các yếu tố như sự suy giảm quy trình hoặc các yếu tố không thể kiểm soát khác trong quá trình sản xuất có thể làm gián đoạn quá trình sản xuất của lô hàng. Để giải quyết những vấn đề thực tiễn này, bài báo tích hợp thời gian kiểm tra và sự cố của các thiết bị sản xuất vào một mô hình tồn kho sản xuất không hoàn hảo với việc chỉnh sửa, trong đó thời gian chạy sản xuất là biến quyết định và quá trình kiểm tra tiếp tục ngay cả sau khi kết thúc một đợt sản xuất; bài báo chứng minh những ảnh hưởng đáng kể đến các giải pháp tối ưu, với việc không cho phép xảy ra thiếu hụt. Dưới những giả định này, một mô hình toán học được rút ra, và tính lõm của hàm lợi nhuận tổng mong đợi được chứng minh. Chính sách tối ưu được thu nhận bằng cách áp dụng phương pháp phân tích. Các trường hợp đặc biệt của mô hình được nghiên cứu và một ví dụ số với phân tích nhạy cảm được cung cấp để rút ra các nhận thức. Hơn nữa, ví dụ số này được sử dụng để so sánh các trường hợp chung và đặc biệt.

In the last two decades a large number of mathematical models have been developed and used for simulating and predicting the unsaturated flow in non — cultivated and cultivated soils. It is the purpose of this paper to show the dynamics of these models and also to present a model that has been developed in the Laboratory of General and Agricultural Hydraulics and Land Reclamation of the School of Agriculture. The model is based on the numerical solution of the partial differential equation that describes the water movement in the unsaturated zone of a cultivated soil. It can predict the water regime of the soil profile taking into account only external to the soil system data (preceding irrigation, precipitation, meteorological data etc.). Therefore it can constitute a very useful tool for irrigation scheduling by the managers of big cooperative irrigation networks. The model has been used to predict the water balance in several farms cultivated with cotton and sugar beets with very good results.

The integrated harvest-scheduling model addresses the tactical forest management planning problem of maximizing harvest revenues minus road construction and transportation costs. This paper considers the problem of developing innovations to this model such that it can: (1) be used to generate solutions to problem instances containing a large set of candidate roads, with many circuits; (2) yield improved solutions when compared to prior formulations; and (3) achieve improvements in the solutions by reducing the total construction and transportation costs. To the end, a new formulation of the integrated model was developed using the following strategy: (a) each candidate road was represented in the model by two directed arcs (instead of one undirected edge, as used in prior formulations); and (b) a set of strengthening constraints including clique constraint was developed to exploit the property of the directness of the candidate roads. The new model was tested and compared with prior formulations on eight problem instances, ranging in size from 900 to 4900 stands and containing candidate roads ranging in number from 3424 to 19,184. Results show that the new formulation: (1) entails the use of larger set of constraints than prior formulations; (2) produced tighter root-LP gaps, than prior models, as the problem instances grew in size and complexity; and (3) produced solutions with the tightest relative gap, the highest objective function value, and major reductions in the cost of constructing a road network, as the problem instances grew in size and complexity. Our conclusion is that the strategy of formulating the integrated model, used in this paper, may be useful to future researchers and practitioners working on this problem.

Environmental education is an important means for the protection of the natural environment. Information and Communication Technologies (ICTs) support various educational tasks, especially with the aim of WWW environments. Information for environmental education projects about the forest can be acquired through Forest Service. Thus, it is developed a model web site to use as a template for any Forest Service unit, with organized material about the forest, about: historical information and status, forest as an ecosystem, functions and benefits, threats and effects, Forest Service, aims and targets and finally links for further information. The application is structured in a flexible, friendly and appealing arrangement for the enduser, comprises a large amount of reliable information, it meets the needs of various users and projects, it promotes environmental awareness and finally upgrades the role of Forest Service through its contribution in environmental education projects.

We study a single machine scheduling problem, where the goal is to maximize the weighted number of jobs completed exactly at their due-dates. The option of job-rejection is considered, i.e., the scheduler may perform only a subset of the jobs. An upper bound on the total permitted rejection cost is assumed. The problem is proved to be NP-hard, and a pseudo-polynomial dynamic programming algorithm is introduced. Our numerical tests indicate that the proposed algorithm performs well: medium size instances (of up to 100 jobs) are solved in less than 1 s.

We consider the problem of minimizing the sum of completion times in a two-machine permutation flowshop problem subject to release dates. We derive several lower bounds as well as a branch-and-bound algorithm for the problem under consideration. Computational experiments, on a large set of randomly generated instances, provide evidence that the proposed procedure performs consistently well.