Beyond Markowitz with multiple criteria decision aiding

The paper is about portfolio selection in a non-Markowitz way, involving uncertainty modeling in terms of a series of meaningful quantiles of probabilistic distributions. Considering the quantiles as evaluation criteria of the portfolios leads to a multiobjective optimization problem which needs to be solved using a Multiple Criteria Decision Aiding (MCDA) method. The primary method we propose for solving this problem is an Interactive Multiobjective Optimization (IMO) method based on so-called Dominance-based Rough Set Approach (DRSA). IMO-DRSA is composed of two phases: computation phase, and dialogue phase. In the computation phase, a sample of feasible portfolio solutions is calculated and presented to the Decision Maker (DM). In the dialogue phase, the DM indicates portfolio solutions which are relatively attractive in a given sample; this binary classification of sample portfolios into ‘good’ and ‘others’ is an input preference information to be analyzed using DRSA; DRSA is producing decision rules relating conditions on particular quantiles with the qualification of supporting portfolios as ‘good’; a rule that best fits the current DM’s preferences is chosen to constrain the previous multiobjective optimization in order to compute a new sample in the next computation phase; in this way, the computation phase yields a new sample including better portfolios, and the procedure loops a necessary number of times to end with the most preferred portfolio. We compare IMO-DRSA with two representative MCDA methods based on traditional preference models: value function (UTA method) and outranking relation (ELECTRE IS method). The comparison, which is of methodological nature, is illustrated by a didactic example.     

Indifference mapping for multiple criteria decisions

Indifference mapping uses multi dimensional scaling techniques to allocate multi criteria policies to points in a space based on an input which consists of those pairs of policies which are equally attractive. The paper takes sets of policies for each of which a single value has been pre-assigned and maps them in two dimensions by applying a probability law to the assessment of indifferent pairs. The paper shows that the maps can be used both to deduce the original value of each policy and can also deduce the probability law which was applied.     

The indifference band in multiple criteria decision problems

A case study of a discrete multiobjective problem using the ‘Indifference Band’ approach is presented. An outranking relation among the various alternatives was obtained and compared with the management's own ranking. It was found that the ‘Indifference Band’ approach can be used in ranking procedures.     

Stock screening with use of multiple criteria decision making and optimization

A new method for the stock ranking based on the multiple criterion decision making and optimization is proposed. Two general criteria are used in the analysis. The first of them is based on the financial indices and may be treated as the criterion of firm's “health” or its financial performance. The second one is the two-criteria performance of firm based on the stock prices. It represents the firm's market success. The method rests on the selection of the stocks with a great correlation of the firm's financial performance and its market success. The local criteria are built in the form of the membership function of corresponding fuzzy subsets. Two different strategies for stock ranking and three most popular methods for local criteria aggregation are compared. As the example the values of financial rations and prices from database comprising the data of 162 firms from subsector of the biotechnology of US economy were used. It is shown that the proposed method makes it possible to select a small group of “good” stocks characterized by a great coincidence of firm's financial performance and its market success. The method rejects from the consideration all the “unsafe” firms, i.e., such ones that their market success is based rather on the public relations, rumors and other rather unreliable information. The method is addressed to those who prefer to select for a portfolio only the firms which demonstrate the closeness of their overall financial performance in the past year and success in the Stock Exchange in the following year.     

An inventory model with random discount offerings

We consider an inventory model in which a supplier makes deal offers with random discount prices at random points in time. Assuming that discount offerings follow a Poisson process and discount price is a discrete random variable with a known distribution, we propose a continuous-review control policy for the model and derive optimality conditions for the policy parameters. The model is then extended to the case of multiple suppliers that offer discount deals with supplier-specific Poisson processes and discount prices. Numerical examples are presented to demonstrate cost savings due to discount offers.     

Personnel selection criteria in IT ventures: A policy-capturing analysis

Growing ventures need to hire new employees and thus enhance their human capital stock. Selecting the right employees is crucial for the firms’ success. This paper looks at the criteria used in the selection process, especially at applicant fit, competencies, and social capital. Using a policy-capturing approach on a sample of managers in the German informationtechnology industry, the paper provides empirical evidence of the relationship between firm age and person-organization fit in the selection process. Furthermore, it demonstrates the interaction between two sets of selection criteria: applicant competencies and applicant fit with the formal job-requirements.     

A novel approach to subgraph selection with multiple weights on arcs

In this paper, an extension of the minimum cost flow problem is considered in which multiple incommensurate weights are associated with each arc. In the minimum cost flow problem, flow is sent over the arcs of a graph from source nodes to sink nodes. The goal is to select a subgraph with minimum associated costs for routing the flow. The problem is tractable when a single weight is given on each arc. However, in many real-world applications, several weights are needed to describe the features of arcs, including transit cost, arrival time, delay, profit, security, reliability, deterioration, and safety. In this case, finding an optimal solution becomes difficult. We propose a heuristic algorithm for this purpose. First, we compute the relative efficiency of the arcs by using data envelopment analysis techniques. We then determine a subgraph with efficient arcs using a linear programming model, where the objective function is based on the relative efficiency of the arcs. The flow obtained satisfies the arc capacity constraints and the integrality property. Our proposed algorithm has polynomial runtime and is evaluated in rigorous experiments.

     

Media selection via multiple objective integer programming

Multiple Objective Integer Linear Programming (MOILP) is presented as an aid to media selection. A MOILP analysis approach recognizes the lack of infinite division in media choices and provides the decisionmaker with an efficient set of alternatives. The decisionmaker may then utilize non-quantifiable criteria to make the final media selection or may use the efficient set developed by the MOILP procedure as a screening mechanism. These screened solutions would then be submitted to further analysis to consider interaction effects, non-linearity and so on. The approach is outlined and an illustrative example using somewhat standard data is provided.     

A statistical analysis of graduates' starting salary and employers' selection criteria

In this paper the relationship between employers' selection criteria such as GPA, internship and previous working experience, student activities, graduates' areas of concentration, and gender upon the graduates' starting salary is examined. A rating system is developed by which the graduates' internship and student activities experience are evaluated and determined. A series of simple, reduced, and full regression models are developed and tested. A procedure for model building and adequacy is developed to arrive at the optimal regression model. A sequential analysis and stepwise regression are utilized to corroborate the adequacy of the proposed regression model. The optimal regression model consists of GPA, computer science concentration, and the graduate's gender. A series of validity tests is performed to support and validate the assumptions made throughout the paper. In conclusion, additional perspectives and analyses are presented.     

Third-party logistics selection problem: A literature review on criteria and methods

This paper presents a literature review on Third-Party Logistics (3PL) selection decision in terms of criteria and methods. Based on the analysis of 67 articles published within 1994–2013 period, this review reveals that 3PL selection is empirical in nature and is related to a region/country, industrial sector, and logistics activities outsourced. In terms of 3PL selection criteria, 11 key criteria are identified; each one is defined by a set of attributes. Cost is the most widely adopted criterion, followed by relationship, services, and quality. In terms of methods for 3PL evaluation, they can be categorized in 5 groups, namely: MCDM techniques, statistical approaches, artificial intelligence, mathematical programming, and hybrid methods.     

Demand switching criteria for multiple products: An inventory cost analysis

In this paper, we consider the problem of demand switching and show how a firm can take advantage of the risk-pooling effect to gain more profit. We examine the case of three products under various switching criteria; a model based on the heuristic approach is developed to determine the switching paths and the corresponding switching rates that yield the optimal profit. A constrained model with limited amount of the switched demand is also developed. In general, the profit increases as a result of higher profit margin or smaller demand variation and correlation. Our result indicates that the profit does not necessarily increase as the switching rate increases; in some cases the profit may even decrease as a result of demand switching. Numerical examples are also included to illustrate the derived models. The developed analytical approach may help practitioners to gain more insight in demand switching and facilitate inventory related decision-making process as well.     

Methods for comparing policies using multiple criteria: an urban example

This paper looks at a variety of methods that can be used in evaluating a set of alternate policies using multiple criteria. The methods examined are the structural mapping of indifferences, utility values, lexicographic ordering, factor analysis, concordance analysis and multidimension scaling. Each method is tested using hypothetical data for a problem in which alternative policies are proposed for allocating monies to housing and health projects in a town. The aim is to try to reveal as objectively as possible, a set of preferred alternatives from which one can be chosen in the political decision-making process. After describing and testing the methods individually, they are compared both on the basis of their results and on the principles involved in their approach. Conclusions about the validity of each method are given, and it is emphasized that all methods should only be used as aids in the choice of an optimal policy.     

Assembly Systems with Sequential Supplier Decisions and Uncertain Demand

We consider multitier push assembly systems with sequential supplier decisions and a wholesale price contract. We show that both an Original Equipment Manufacturer (OEM)–Contract Manufacturer (CM) assembly and a modular assembly with sequential supplier decisions are mathematically equivalent to the corresponding traditional assembly. We determine that, in most cases, the first mover supplier realizes a higher profit than the second mover supplier but we also identify the sufficient conditions for the reverse to occur. We provide conditions under which the order quantity, the second mover profit, total supplier profits, and the assembler profit are either higher or lower for a multitier system with sequential suppliers compared to simultaneous suppliers. We conclude that the first mover is always better off in a three‐tier sequential system while she can be either better off or worse off in a four‐tier sequential system compared to the corresponding simultaneous systems. We also analyze the impact of information asymmetry on the supplier and assembler profits in a three‐tier sequential system. Finally, we determine the profit threshold for an independent manufacturer in a three‐tier system to become a CM in a four‐tier system and vice versa.     

Sourcing Decisions with Stochastic Supplier Reliability and Stochastic Demand

Supplier sourcing strategies are a crucial factor driving supply chain success. In this paper, we investigate the implications of uncertain supplier reliability on a firm's sourcing decisions in an environment with stochastic demand. In particular, we characterize specific conditions under which a firm should choose a single versus multiple supplier sourcing strategy. In an environment with both uncertain demand and supply, we characterize the total order quantity, the number of suppliers selected for order placement, and the allocation of the total order quantity among these selected suppliers. For deeper managerial insight, we also examine the sensitivity of the optimal sourcing decisions to interactions between uncertainties in product demand and supply reliability. We show that sourcing from a single supplier is an optimal strategy for environments characterized by high levels of demand uncertainty or high salvage values. A numerical analysis based on data obtained from an office products retailer further reinforces our analytical results. In addition, we also find that when minimal order quantities are imposed, there are situations where it is not optimal to place an order with the lowest cost supplier.     

A multiple criteria decision-making model for justifying the acceptance of rush orders

Rush orders are immediate customer demands that exceed the expectation of a currently effective MPS (master production schedule). Decision-makers are often hesitant in the decision of accepting such orders. This paper presents a multiple criteria decision-making model for justifying the acceptance of rush orders for an assembly-to-order production system. Four criteria or production objectives are simultaneously considered and a multiple objective programming technique, the e-constraints approach, is adopted to solve the decision-making problem. This model could give the cost estimation for producing a rush order under various combinations of production objectives. The computed cost value could serve as a valuable reference for justifying the economics of accepting the rush order, and help to determine its pricing strategy.