Our focus herein is on developing an effective taxonomy for the simultaneous and real-time management of supply and demand chains. More specifically, the taxonomy is developed in terms of its underpinning components and its research foci. From a components perspective, we first consider the value chain of supplier, manufacturer, assembler, retailer, and customer, and then develop a consistent set of definitions for supply and demand chains based on the location of the customer order penetration point. From a research perspective, we classify the methods that are employed in the management of these chains, based on whether supply and/or demand are flexible or fixed. Interestingly, our taxonomy highlights a very critical research area at which both supply and demand are flexible, thus manageable. Simultaneous management of supply and demand chains sets the stage for mass customization which is concerned with meeting the needs of an individualized customer market. Simultaneous and real-time management of supply and demand chains set the stage for real-time mass customization (e.g., wherein a tailor first laser scans an individual’s upper torso and then delivers a uniquely fitted jacket within a reasonable period, while the individual is waiting). The benefits of real-time mass customization can not be over-stated as products and services become indistinguishable and are co-produced in real-time, resulting in an overwhelming economic advantage.

The revealed preference is a central subject in classical consumer theory. Authors like Samuelson, Arrow, Richter, Sen, Uzawa and others have proposed an axiomatic setting of revealed preference theory.

Consequently revealed preference axioms WARP and SARP and congruence axioms WCA and SCA have been considered.

An important theorem of Sen establishes the equivalence between these axioms provided the family of budgets includes all non-empty finite sets of bundles.

Fuzzy consumer theory (=fuzzy choice functions) is a topic that appears in a lot of papers. Particularly, Banerjee studies in fuzzy context axioms of revealed preference and congruence extending some results of Arrow and Sen.

In this paper we modify the Banerjee definition of a fuzzy choice function (=fuzzy consumer) and we study some fuzzy versions of the axioms of revealed preference and congruence. Banerjee fuzzifies only the range of a consumer; we use a fuzzification of both the domain and the range of a consumer. The axioms WAFRP, SAFRP, WFCA, SFCA generalize to fuzzy consumer theory the well-known axioms WARP, SARP, WCA, SCA. Our main result establishes some connections between WAFRP, SAFRP, WFCA, SFCA extending a significant part of Sen theorem.

Generally, we work in a fuzzy set theory based on a continuous t-norm, but some results are obtained for Gödel t-norm and others are obtained for Lukasiewicz t-norm.

High volume conveyor systems in distribution centers have very large footprint and can handle large volumes and hold thousands of items. Traditional discrete-event cell-based approach to simulate such networks becomes computationally challenging. An alternative approach, in which the traffic is represented by segments of fluid flow of different density instead of individual packages, is presented in this paper to address this challenge. The proposed fluid-based simulation approach is developed using a Hybrid Petri Nets framework. The underlying model is a combination of an extension of a Batches Petri Nets (BPN) and a Stochastic Petri Nets (SPN). The extensions are in the inclusion of random elements and relaxation of certain structural constraints. Some adaptations are also made to fit the target system modeling. The approach is presented with an example.

The basic purpose of a quality loss function is to evaluate a loss to customers in a quantitative manner. Although there are several multivariate loss functions that have been proposed and studied in the literature, it has room for improvement. A good multivariate loss function should represent an appropriate compromise in terms of both process economics and the correlation structure among various responses. More important, it should be easily understood and implemented in practice. According to this criterion, we first introduce a pragmatic dimensionless multivariate loss function proposed by Artiles-Leon, then we improve the multivariate loss function in two respects: one is making it suitable for all three types of quality characteristics; the other is considering correlation structure among the various responses, which makes the improved multivariate loss function more adequate in the real world. On the bases of these, an example from industrial practice is provided to compare our improved method with other methods, and last, some reviews are presented in conclusion.

The Vehicle Routing Problem with Time Windows is a generalization of the well known capacity constrained Vehicle Routing Problem. A homogeneous fleet of vehicles has to service a set of customers. The service of the customers can only start within a well-defined time interval denoted the time window. The objective is to determine routes for the vehicles that minimizes the accumulated cost (or distance). Currently the best approaches for determining optimal solutions are based on column generation and Branch-and-Bound, also known as Branch-and-Price. This paper presents two ideas for run-time improvements of the Branch-and-Price framework for the Vehicle Routing Problem with Time Windows. Both ideas reveal a significant potential for run-time refinements when speeding up an exact approach without compromising optimality.

This paper considers scheduling n jobs on a single machine where the job processing times and due dates are independent random variables with arbitrary distribution functions. We consider the case that the weighted job tardiness in expectation is minimized. It is assumed that job’s due dates are compatible with processing times and weights. We show that the jobs should be sequenced in decreasing stochastic order of their due dates.

The general theory of the ANP enables one to deal with the benefits, opportunities, costs, and risks (the BOCR merits) of a decision, by introducing the notion of negative priorities for C and R along with the rating (not comparison) of the top priority alternative synthesized for each of the four merits in terms of strategic criteria to enable one to combine the four B, O, C, and R values of each alternative into a single outcome. Strategic criteria are very basic criteria individuals and groups use to assess whether they should make any of the many decisions they face in their daily operations. They do not depend on any particular decision for their priorities but are assessed in terms of the goals and values of the individual or organization. Synthesis is made with two formulas, one multiplicative and one additive subtractive that can give rise to negative overall priorities. This paper summarizes and illustrates basic complex decisions involving several control criteria under each of the BOCR merits.