in this paper, a genetic algorithm is presented for an identical parallel-machine scheduling problem with family setup time that minimizes the total weighted flow time ( ). no set-up is necessary between jobs belonging to the same family. a set-up must be scheduled when switching from the processing of family i jobs to those of another family j, i  j, the duration of this set-up being the sequ...

hub covering problem (hlp) is a very popular areas of research for its wide ranges of applications in different service or manufacturing industries. this paper considers a bi-objective hub covering location problem with congestion. the objectives minimize the total transportation cost and the total waiting time for all hobs, respectively. the resulted multi-objective decision-making problem is ...

Large scale dispatching problems are technically characterized as classical NP-hard problems which means that they cannot be solved optimally with existing methods in a polynomial time. Benders decomposition is recommended for solving large scale Mixed Integer Programming (MIP). In this paper we use the Bender Decomposition technique for reformulating the Ready Mixed Concrete Dispatching Proble...

As a part of the day-ahead market clearing process, Midcontinent Independent System Operator (MISO) solves one of the largest and most challenging Security Constrained Unit Commitment (SCUC) models. Better computational performance of SCUC models not only improves the market efficiency but also facilitates future market development. This paper introduces two developments on Mixed Integer Progra...

We propose an approach based on mixed integer programming (MIP) with decomposition to solve a workforce scheduling and routing problem, in which a set of workers should be assigned to tasks that are distributed across different geographical locations. This problem arises from a number of home care planning scenarios in the UK, faced by our industrial partner. We present a mixed integer programm...

‎In this paper‎, ‎some KKT type sufficient global optimality conditions‎ ‎for general mixed integer nonlinear programming problems with‎ ‎equality and inequality constraints (MINPP) are established‎. ‎We achieve‎ ‎this by employing a Lagrange function for MINPP‎. ‎In addition‎, ‎verifiable sufficient global optimality conditions for general mixed‎ ‎integer quadratic programming problems are der...

The design of telecommunication network with capacity constraints of links, routers and ports of routers is considered in this paper. Specially, we limit each demand flow traversed through a pre-specified maximal number of links (called hops) under node failure scenarios in IP layer network. Such a design must be the most cost-effective and ensure that feasible flows continue to exist even when...

A core technique of modern tools for formally reasoning about computing systems is generating and dispatching queries to automated theorem provers, including Satisfiability Modulo Theories (SMT) provers. SMT provers aim at the tight integration of decision procedures for propositional satisfiability and decision procedures for fixed first-order theories – known as theory solvers. This thesis pr...

although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. but, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. this paper considers the problem of scheduling no-idle hybrid flow shops. a mixed integer linear programming model is first developed to mathematically form...

This paper presents a grid-enabled system for solving large-scale mixed integer programming (MIP) problems. The system has been developed using Globus and MPICH-G2, and consists of two solvers and of an interface portal. After a brief introduction to Branch, Cut and Price optimization algorithms, the paper focuses on the system architecture, solvers and portal user interface. The performance of...