Considering the standard particle swarm optimization (PSO) has the shortcomings of low convergence precision in job shop scheduling problems, the job shop scheduling solution is presented based on improved particle swarm optimization (A-PSO). In this paper, the basic theory of A-PSO is described. Also, the coding and the selection of parameters as well as the decoding of A-PSO are studied. It u...

We consider a robotic ow shop model in which a single robot is responsible for the transportation of parts between machines. For reasons of simplicity, when the shop is to produce a large number of identical parts, the robot usually performs repeatedly a xed sequence of activities. This sequence of activities is called a 1-unit cycle if each execution of the sequence results in the production o...

The flexible job shop scheduling problem is a well-known combinatorial optimization problem. This paper proposes an improved shuffled frog-leaping algorithm to solve the flexible job shop scheduling problem. The algorithm possesses an adjustment sequence to design the strategy of local searching and an extremal optimization in information exchange. The computational result shows that the propos...

We study the special case of the m machine ow shop problem in which the processing time of each operation of job j is equal to p j ; this variant of the ow shop problem is known as the proportionate ow shop problem. We show that for any number of machines and for any regular performance criterion we can restrict our search for an optimal schedule to permutation schedules. Moreover, we show that...

SOMMARIO/ABSTRACT In this paper we report on the extension of the classical HTN planner SHOP to plan in partially observable domains with uncertainty. Our algorithm PC-SHOP uses belief states to handle situations involving incomplete and uncertain information about the state of the world. Sensing and acting are integrated in the primitive actions through the use of a stochastic model. PC-SHOP i...

Dynamic job shop scheduling that considers random job arrivals and machine breakdowns is studied in this paper. Considering an event driven policy rescheduling, is triggered in response to dynamic events by variable neighborhood search (VNS). A trained artificial neural network (ANN) updates parameters of VNS at any rescheduling point. Also, a multi-objective performance measure is applied as o...

In this paper the flow shop scheduling problem with minimizing two criteria simultaneously is consider. Selected criteria are: makespan and the sum of tardiness of jobs. For each separate criteria the problem is strongly NP-hard, which makes it NP-hard as well. There is a number of heuristic algorithms to solve the flow shop problem with various single objectives, but heuristics for multi-crite...

This is a summary of the journal article (Malapert et al. 2012) published by Journal on Computing entitled “An Optimal Constraint Programming Approach to the Open-Shop Problem”. The article presents an optimal constraint programming approach for the Open-Shop scheduling problem, which integrates recent constraint propagation and branching techniques with new upper bound heuristics. Randomized r...

In this paper we consider a repair shop location problem with uncertainties in demand. New local repair shops have to be opened at a number of locations. At these local repair shops, customers arrive with broken, but repairable, items. Customers go to the nearest open repair shop. Since they want to leave as soon as possible, a (small) inventory of working items is kept at the repair shops. A c...

BACKGROUND Throughout Africa, many people seek care for malaria in private-sector drug shops where diagnostic testing is often unavailable. Recently, subsidized artemisinin-based combination therapies (ACTs), a first-line medication for uncomplicated malaria, were made available in these drug shops in Tanzania. This study assessed the prevalence of malaria among and purchase of ACTs by drug sho...