Stochastic make-to-stock inventory deployment problem: an endosymbiotic psychoclonal algorithm based approach

Integrated steel manufacturers (ISMs) have no specific product, they just produce finished product from the ore. This enhances the uncertainty prevailing in the ISM regarding the nature of the finished product and significant demand by customers. At present low cost mini-mills are giving firm competition to ISMs in terms of cost, and this has compelled the ISM industry to target customers who want exotic products and faster reliable deliveries. To meet this objective, ISMs are exploring the option of satisfying part of their demand by converting strategically placed products, this helps in increasing the variability of product produced by the ISM in a short lead time. In this paper the authors have proposed a new hybrid evolutionary algorithm named endosymbiotic-psychoclonal (ESPC) to decide what and how much to stock as a semi-product in inventory. In the proposed theory, the ability of previously proposed psychoclonal algorithms to exploit the search space has been increased by making antibodies and antigen more co-operative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results compared with other evolutionary algorithms such as genetic algorithms (GA) and simulated annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained and convergence time required to reach the optimal/near optimal value of the solution

Do Quasi-Hyperbolic Preferences Explain Academic Procrastination? An Empirical Evaluation

Traditional neoclassical thought fails to explain questions such as problems of self-control. Behavioural economics have explained these matters on the basis of the intertemporal preferences of individuals and, specifically, the so-called (β, δ) model which emphasises present bias. This opens the way to the analysis of new situations in which people can adopt incorrect indecisions that make it necessary for the government to intervene. The literature which has developed the (β, δ) model and its implications has generated a categorisation of people that is widely used but which lacks a systematic empirical evaluation. It is important to value the need for this public action. In this article, we develop a method which makes it possible to verify the main implications that this model has to explain the procrastination of university students. Using an experimental time discount task with real monetary incentives, we estimate the students’ β and δ parameters and we analyse their correlation with their answers to a series of questions concerning how they plan to study for an exam. The results are ambiguous given that they back some of the model’s conclusions but reject others, including a number of the most basic ones, such as the relation between present biases and some of the categories of people, these being essential to predict their behaviour

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Endogenous Time-Dependent Rules and Inflation Inertia

In this paper we endogenize fixed price time-dependent rules to examine the output effects of monetary disinflation. We derive the optimal rules in and out of inflationary steady states, and develop a methodology to aggregate individual pricing rules which vary through time. Because of strategic complementarities we have to solve both problems simultaneously. This allows us to reassess the output costs of monetary disinflations, including aspects such as the roles of the initial level of inflation, and of the degree of strategic complementarity in price. Finally, we relax the strict assumption of pure time-dependent rules by allowing price setters to reevaluate their rules at the time disinflation is announced.

The Life-Cycle Permanent-Income Model and Consumer Durables

This paper presents an extension of the life-cycle permanent-income model of consumption to the case of a durable good whose purchase involves lumpy trans- actions costs. Where individual behavior is concerned, the implications of the model are different in some respects from those of standard consumption theory. Specifically, rather than choose an optimal path for the service flow from durables, the optimizing consumer will choose an optimal range and try to keep his service flow inside that range. The dynamics implied by this behavior is different from that of the stock adjustment model. Properties of aggregate durables consumption are derived by explicit aggregation. In particular, it is shown that expenditures on durables display very large short-run elasticity to changes in permanent income. Empirical tests of the sort suggested by Hall (1978) generally produce results that are in line with the predictions of the theory.

Postponing Branching Decisions

Solution techniques for Constraint Satisfaction and Optimisation Problems often make use of backtrack search methods, exploiting variable and value ordering heuristics. In this paper, we propose and analyse a very simple method to apply in case the value ordering heuristic produces ties: postponing the branching decision. To this end, we group together values in a tie, branch on this sub-domain, and defer the decision among them to lower levels of the search tree. We show theoretically and experimentally that this simple modification can dramatically improve the efficiency of the search strategy. Although in practise similar methods may have been applied already, to our knowledge, no empirical or theoretical study has been proposed in the literature to identify when and to what extent this strategy should be used.Comment: 11 pages, 3 figure

Managing the trade-off implications of global supply

The cost versus response trade-off is a growing logistics issue due to many markets being increasingly characterized by demand uncertainty and shorter product life cycles. This is exacerbated further with supply increasingly moving to low cost global sources. However, the poor response implications of global supply are often not addressed or even acknowledged when undertaking such decisions. Consequently, various practical approaches to minimising, postponing or otherwise managing the impact of the demand uncertainty are often only adopted retrospectively. Even though such generic solutions are documented through case examples we lack effective tools and concepts to support the proactive identification and resolution of such trade-offs. This paper reports on case-based theory building research, involving three cases from the UK and USA used in developing a conceptual model with associated tools, in support of such a process