This paper proposes a dynamic lexicographic approach to tackle multi-objective optimization problems. In this method, the ordering of objectives, which reflects their relative preferences, is changed in a dynamic fashion during the search. This approach eliminates the need for the decision-maker to establish fixed preferences among the competing objectives, which is often difficult. At the same...

Scheduling and timetabling problems are multi-constrained constraint satisfaction problems that have huge search space. These problems are NP hard. This paper investigates the use of backtracking approaches to laboratory personnel scheduling problem in which the objective is to assign tasks to employees. The main objective of this work is to search for better solutions than those obtained by au...

We introduce a stochastic dynamic optimization problem, where risk aversion is expressed by a stochastic ordering constraint. The constraint requires that a random reward sequence depending on our decisions dominates a given benchmark random sequence. The dominance is defined by discounting both processes with a family of discount sequences, and by applying a univariate order. We describe the g...

Reconstructing a physical map of a chromosome from a genomic library presents a central computational problem in genetics. Physical map reconstruction in the presence of errors is a problem of high computational complexity which provides the motivation for parallel computing. Parallelization strategies for a maximum likelihood estimation-based approach to physical map reconstruction are present...

Reconstructing a physical map of a chromosome from a genomic library presents a central computational problem in genetics. Physical map reconstruction in the presence of errors is a problem of high computational complexity that provides the motivation for parallel computing. Parallelization strategies for a maximum-likelihood estimation-based approach to physical map reconstruction are presente...

We present a new local optimizer called SOP-3-exchange for the sequential ordering problem that extends a local search for the traveling salesman problem to handle multiple constraints directly without increasing computational complexity. An algorithm that combines the SOP-3-exchange with an Ant Colony Optimization algorithm is described and we present experimental evidence that the resulting a...

We propose an extension of Newton’s Method for unconstrained multiobjective optimization (multicriteria optimization). The method does not scalarize the original vector optimization problem, i.e. we do not make use of any of the classical techniques that transform a multiobjective problem into a family of standard optimization problems. Neither ordering information nor weighting factors for the...

this paper is a research on the ordering planning of a supply chain with one supplier, multi buyer and multi deteriorating items. items have fixed life time and expire dates. the ordering period is taken as variable and must be computed the proposed models. the problem is studied via two different approaches the first is the joint replenishment, based on the hwang and chew's model [3] and ...

For digraphs G and H, a homomorphism of G to H is a mapping f : V (G)→V (H) such that uv ∈ A(G) implies f(u)f(v) ∈ A(H). If moreover each vertex u ∈ V (G) is associated with costs ci(u), i ∈ V (H), then the cost of a homomorphism f is ∑ u∈V (G) cf(u)(u). For each fixed digraph H, the minimum cost homomorphism problem for H, denoted MinHOM(H), is the following problem. Given an input digraph G, ...