Abstract The paper is motivated by real problems concerning tasks assignment to workers in medium-sized upholstered furniture plants managed using the Demand-Driven Manufacturing. Although methodology was developed for it can be applied other types of production plants. We involve competence coefficients, which describe level worker’s skills or capabilities perform a specific task. coefficients...

We consider a convex integer program which is a nonlinear version of the assignment problem. This problem is reformulated as an equivalent problem. An algorithm for solving the original problem is suggested which is based on solving the simple assignment problem via some of known algorithms.

In this paper we present a local search heuristic method for an integrated airline scheduling, fleeting and pricing model. The integrated model simultaneously optimizes the decisions of schedule design, fleet assignment, seat allocation, pricing and considers passengers’ spill and recapture. The resulting problem is a mixed integer non-convex problem due to the explicit representation of a dema...

This paper deals with the assignment of a type of task to each member of a multi-function staff (each worker is able to perform a given subset of types of tasks, possibly with a priority index associated to each element of the subset). The resulting number of workers for each type of task must be not less than a given lower bound and as close as possible to another given value. The objectives a...

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minim...

In this paper we consider the programming of job rotation in the Assembly Line Worker Assignment and Balancing Problem. The motivation for this study comes from the designing of assembly lines in sheltered work centers for the disabled, where workers have different task execution times. In this context, the well-known training aspects associated with job rotation are particularly desired. We pr...

The cardinality constraint is an intrinsic way to restrict the solution structure in many domains, for example, sparse learning, feature selection, and compressed sensing. To solve a cardinality constrained problem, the key challenge is to solve the projection onto the cardinality constraint set, which is NP-hard in general when there exist multiple overlapped cardiaiality constraints. In this ...