Stochastic flexible flow shop scheduling problem (SFFSSP) is one the main focus of researchers due to the complexity arises from inherent uncertainties and also the difficulty of solving such NP-hard problems. Conventionally, in such problems each machine’s job process time may encounter uncertainty due to their relevant random behaviour. In order to examine such problems more realistically, fi...

We present a family of data-reusing and affine projection algorithms. For identification of a noisy linear finite impulse response channel, a partial knowledge of a channel, especially noise, can be used to improve the performance of the adaptive filter. Motivated by this fact, the proposed scheme incorporates an estimate of a knowledge of noise. A constraint, called the adaptive noise constrai...

It is generally assumed that the variables, domains and constraints of a Finite-Domain Constraint Satisfaction Problem are all pre-computed inputs to a black-box constraint satisfaction algorithm. The obvious advantages of such an assumption is the freedom in developing generic constraint solvers and the declarative use of constraint technology. However, it is useful to examine applications of ...

In this paper, a bi-objective model is proposed for designing a pre-positioning network of pharmaceutical supplies considering their limited shelf-life. The presented model aims to consider both cost efficiency and responsiveness by minimization of total cost and the maximum amount of unmet demand under uncertainties in demand and supply sides’ data. Moreover, for effective distribution of reli...

For planning to come of age, plans must be judged by a measure of quality, such as the total cost of actions. This paper describes an optimal-cost planner which guarantees global optimality whenever the planning problem has a solution. We code the extraction of an optimal plan, from a planning graph with a fixed number k of levels, as a weighted constraint satisfaction problem (WCSP). The speci...

In this paper, we study the problem of constructing an energy efficient data aggregation tree for data gathering in wireless sensor networks. We consider a real-time scenario where the data aggregation must be performed within a specified latency constraint. The objective is to minimize the overall energy cost of the sensor nodes in the aggregation tree subject to the latency constraint. We pro...

In order to improve the sparsity exploitation performance of norm constraint least mean square (LMS) algorithms, a novel adaptive algorithm is proposed by introducing a variable p-norm-like constraint into the cost function of the LMS algorithm, which exerts a zero attraction to the weight updating iterations. The parameter p of the p-norm-like constraint is adjusted iteratively along the negat...

In this paper we study the computational complexity of the (extended) minimum cost homomorphism problem (Min-Cost-Hom) as a function of a constraint language, i.e. a set of constraint relations and cost functions that are allowed to appear in instances. A wide range of natural combinatorial optimisation problems can be expressed as Min-Cost-Homs and a classification of their complexity would be...

This paper considers a multi-period, multi-product inventory-routing problem in a two-level supply chain consisting of a distributor and a set of customers. This problem is modeled with the aim of minimizing bi-objectives, namely the total system cost (including startup, distribution and maintenance costs) and risk-based transportation. Products are delivered to customers by some heterogeneous ...

This study presents a multimodal hub location problem which has the capability to split commodities by limited-capacity hubs and transportation systems, based on the assumption that demands are stochastic for multi-commodity network flows. In the real world cases, demands are random over the planning horizon and those which are partially fulfilled, are lost. Thus, the present study handles dema...