高风险、高成本背景下棉农种植决策分析

依据对新疆自治区及新疆生产建设兵团341户棉农调查,通过分别构建Logit二元选择模型,分析在高市场风险、高生产成本等复杂背景下,棉农种植决策差异。研究结果表明,户主年龄、种植面积、亩均成本、棉花单产、种植经验、对成本预期6项指标对兵团及自治区棉农种植决策均有着显著影响。不同的是棉花收入占家庭总收入比重仅在自治区模型中通过显著性检验,而是否机采也仅在兵团模型中通过了显著性检验。文章基于此实证结果并结合相关理论分析,提出促进棉农积极植棉,增收的相关建议。     

矩形件排样的流程和算法设计

针对人工矩形件排样效率低、耗时长,且不能保证得到板材利用率为最优方案的问题,通过研究人工矩形件排样 的过程,提出了一种下料系统流程和矩形件排样的启发式与遗传相结合的算法。研究结果表明：所设计的下料系统流程 能够充分利用原材料库和余料库,且避免生成更多的余料;通过文中设计的启发式和遗传相结合的矩形件排样算法,能 够快速搜索出近似总体最优的排样方案。该设计方案能够提高板材利用率,同时减少更多余料的产生。     

Adaptive PORT–MVRB estimation: an empirical comparison of two heuristic algorithms

In this article, we deal with an empirical comparison of two data-driven heuristic procedures of estimation of a positive extreme value index (EVI), working thus with heavy right tails. The semi-parametric EVI-estimators under consideration, the so-called peaks over random threshold (PORT)–minimum-variance reduced-bias (MVRB) EVI-estimators, are location and scale-invariant estimators, based on the PORT methodology applied to second-order MVRB EVI-estimators. Trivial adaptations of these algorithms make them work for a similar estimation of other parameters of extreme events, such as the Value-at-Risk at a level p, the expected shortfall and the probability of exceedance of a high level x, among others. Applications to simulated data sets and to real data sets in the field of finance are provided.     

The effects of managerial decision making behaviour and order book size on workload control system implementation in Make-To-Order companies

Insufficient attention has been paid to behavioural influences on the implementation of the ‘Workload Control’ (WLC) concept – a Production Planning and Control (PPC) approach for small and medium sized Make-To-Order companies – and there is an implicit assumption that managers are rationalistic in their decision-making. This paper analyses the effects of both managerial decision-making behaviour and the size of a company’s order book, affecting the number of decisions that have to be made, on two case study implementations of a WLC system. The Recognition-Primed Decision (RPD) model from the Naturalistic Decision-Making literature is used to unpack the first case where implementation failed. This highlighted a misalignment between how the company’s owner-manager initially made operational decisions and how a rationalistic WLC system functions. But the company is studied over six years, allowing us to show how the owner-manager was forced to transition from the RPD model to a more rationalistic approach to PPC as the size of the order book increased. A second case study is then briefly presented in which WLC system implementation was successful; the RPD model was not strongly evident and the size of the order book was greater to begin with. The paper helps to understand the decision-making behaviour of managers in small companies and how it may conflict or be misaligned with the rationalistic assumptions underpinning the WLC concept. This provides a possible explanation for why few successful implementations of the concept have been presented in literature.     

A hybrid approach to sequencing jobs using heuristic rules and neural networks

A hybrid approach to solve job sequencing problems using heuristic rules and artificial neural networks is proposed. The problem is to find a job sequence for a single machine that minimizes the total weighted tardiness of the jobs. Two different cases are considered: (1) when there are no setups, and (2) when there are sequence-dependent setup times. So far, successful heuristic rules for these cases are: apparent tardiness cost (ATC) rule proposed by Vepsalainen and Morton for the former case, and an extended version of the ATC rule (ATCS) proposed by Lee, Bhaskaran, and Pinedo for the latter. Both approaches utilize some look-ahead parameters for calculating the priority index of each job. As reported by Bhaskaran and Pinedo, the proper value of the look-ahead parameter depends upon certain problem characteristics, such as due-date tightness and due-date range. Thus, an obvious extension of the ATC or the ATCS rule is to adjust the parameter values depending upon the problem characteristics: this is known to be a difficult task. In this paper, we propose an application of a neural network as a tool to ‘predict’ proper values of the look-ahead parameters. Our computational tests show that the proposed hybrid approach outperforms both the ATC rule with a fixed parameter value and the ATCS using the heuristic curve-fitting method.     

Durability,Transit Lags,and Optimality of Inventory Management Decisions

Two laboratory experiments on a single‐echelon inventory task show that inventory durability interacts with transit lags to create order volatility that exceeds demand volatility. Thus, inventory durability and transit lags cause managers to deviate from inventory decision optimality. Durability creates a large increase in order volatility because players adjust orders insufficiently to reflect current inventory and backlogs, much as they adjust orders insufficiently to reflect holding and backlog costs in newsvendor studies (e.g., Schweitzer and Cachon 2000). Transit lags exacerbate non‐optimal ordering by interfering with players' ability to correct prior errors. Our results suggest that non‐optimal inventory decisions can be driven by inventory and supply chain characteristics, even in the absence of the coordination and information sharing problems studied by Croson et al. (2005) and Sterman (1989a,b). We also examine the influence of features related to personality. We find little evidence that the interactive effects of durability and transit lags are altered by need for cognition, impulsiveness, or locus of control, suggesting that these features make supply chain management extremely difficult. These results imply that retailers and their upstream partners must consider the characteristics of their product and supply chains when interpreting demand signals received from downstream partners.     

Pricing and Replenishment of Competing Perishable Product Variants under Dynamic Demand Substitution

I consider pricing and ordering decisions faced by a retailer selling a perishable product with a two‐period shelf life over an infinite horizon. In the first period, the product is “new”; in the next, it becomes “old.” The new product is perceived by customers to have a higher quality than the old product. Every period, the retailer makes three decisions: prices for the new and old products and how much new product to order. I first show, with some simple cases, that demand uncertainty can make the sale of the old product profitable. I then consider a more realistic case with dynamic demand substitution among customers. I recognize that the retailer's decisions may be constant or may vary across different periods, under different contexts. For instance, varying the price of the new product can sometimes be difficult due to the negative impact it generates among customers. I find that (i) the benefit obtained from selling the old product with constant decisions is much higher than the benefit from allowing all the decisions to vary; (ii) the former benefit increases with a higher procurement cost, a higher quality of the new product, and higher demand volatility; however, the latter benefit is non‐monotone in these parameters; (iii) most of the latter benefit can be obtained by just changing the order quantity; and (iv) as the inventory of the old product increases, when all the decisions vary, the optimal price of the new product may increase or decrease.     

Group decision making on water resources based on analysis of individual rankings

In problems to do with managing water resources multiple decision makers are involved, each acting in their own right and using different value systems. In the literature on management science, several procedures are proposed in order to establish a collective preference based on the aggregation of different individual preferences. However, the well-known methods that focus on a single winner have some inconveniences that should be addressed. This paper is focused on a group decision making procedure based on the analysis of individual rankings with the aim of choosing an appropriate alternative for a water resources problem. This alternative is found to be the best compromise from the points of view of all actors involved in the decision problem. The structure of the method is set out as is its application to the water resources problem. A comparison with other methods is presented and discussed.     

Multiple criteria decision analysis of treatment and land-filling technologies for waste incineration residues

In this paper, we present a real-world case realized in Switzerland on behalf of the federal agency in charge of the waste policy. The incineration of urban wastes generates hazardous residues that need specific treatment and/or land-filling technologies. The variety of local situations and appraisals led to the choice of very different solutions. Moreover, proponents were keen to propose new technologies. The purpose of this study was to provide the background for a national policy that would apply to all future projects.     

危险品集成物流管理系统选址-选线模型研究

以路网的危险度瓶颈限制为切入点研究了一类危险品集成物流管理系统选址—选线问题,对应于路网危险度瓶颈限制引入安全费用非递减函数,并根据运输工具的安全配置等级构造该等级下的子网络,物流系统的选址—选线结果随着路网的调整而不断变化.危险品集成物流系统的管理存在多个目标,文中首先分析了成本、风险和风险公平性等优化目标,在说明了建模的假设条件后,建立了基于路网危险度瓶颈限制的危险品集成物流系统选址—选线的多目标模型,并根据模型给出了一种启发式算法,最后用一个算例对模型进行了数值演算.