Job Shop Scheduling is an important combinatorial optimisation problem in practice. It usually contains many (four or more) potentially conflicting objectives such as makespan and mean weighted tardiness. On the other hand, evolving dispatching rules using genetic programming has demonstrated to be a promising approach to solving job shop scheduling due to its flexibility and scalability. In th...

The sparse linear method can reduce or expanse the solution range of integer programming problem by using former enumeration method lists all solution space, and then constraining them into a scale, after that picking up optimal solution form this scale. Calculation time will be reduced by using a revised integer programming model based on sparse linear, which can help reduce the number of solu...

This paper considers a scheduling problem in which the objective is to determine an optimal machine speed pair and an optimal schedule. There are two machines A, B and n jobs each of which consists of two operations. One operation is to be processed on machine A and the other on machine B. All jobs are open shop type, i.e., processing order of two operations is not specified and so processing o...

We present optimal solutions to the test scheduling problem for core-based systems. Given a set of tasks (test sets for the cores), a set of test resources (e.g., test buses, BIST hardware) and a test access architecture, we determine start times for the tasks such that the total test application time is minimized. We show that the test scheduling decision problem is equivalent to the -processo...

In order to obtain a solution to a constraint satisfaction problem, constructive methods iteratively extend a consistent partial assignment until all problem variables are instantiated. If the current partial assignment is proved to be inconsistent, it is then necessary to backtrack and perform alternative instantiations. On the other hand, reparative methods iteratively repair an inconsistent ...

This paper addresses the open shop scheduling problem to minimize the total completion time, provided that one of the machines has to process the jobs in a given sequence. The problem is NP-hard in the strong sense even for the two-machine case. A lower bound is derived based on the optimal solution of a relaxed problem in which the operations on every machine may overlap except for the machine...

A variation of preemptive open shop scheduling corresponds to nding a feasible edge coloring in a bipartite multigraph with some requirements on the size of the di erent color classes. We show that for trees with xed maximum degree, one can nd in polynomial time an edge k-coloring where for i = 1; : : : ; k the number of edges of color i is exactly a given number hi, and each edge e gets its co...

This paper involves the study of a simulation based proactive decision support module for the shop-floor scheduling of the Plastic Processing Section (PPS) at Bharti Telecom Limited, Gurgaon, India. The flow of material and information in this shop is highly complex as it involves multiple product parts, sequence dependent setup, molding machine specifications, mould restrictions etc. with a va...

In the multiprocessor open shop scheduling problem, jobs are to be processed on a set of processing centers -each having one or more parallel identical machines, while jobs do not have a pre-specified obligatory route. A special case is the proportionate multiprocessor open shop scheduling problem (PMOSP) in which the processing time on a given center is not job-dependent. Applications of the P...

In this work we consider a multiobjective open shop scheduling problem with uncertain processing times and flexible due dates, both modelled using fuzzy sets. We adopt a goal programming model based on lexicographic multiobjective optimisation of both makespan and due-date satisfaction and propose a particle swarm algorithm to solve the resulting problem. We present experimental results which s...