Job Shop scheduling problem has significant importance in many researching fields such as production management and programming and also combined optimizing. Job Shop scheduling problem includes two sub-problems: machine assignment and sequence operation performing. In this paper combination of particle swarm optimization algorithm (PSO) and gravitational search algorithm (GSA) have been presen...

The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous eeorts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderate...

Bio-Inspired computing is the subset of Nature-Inspired computing. Job Shop Scheduling Problem is categorized under popular scheduling problems. In this research work, Bacterial Foraging Optimization was hybridized with Ant Colony Optimization and a new technique Hybrid Bacterial Foraging Optimization for solving Job Shop Scheduling Problem was proposed. The optimal solutions obtained by propos...

We analyse the interaction between a seller and customers in a shop on the fruits and vegetables wholesale market in Marseille using an unique data set. We find that customers’ bargaining activity is correlated with the kind and location of the business. To determine how the interactions between the seller and the customers influence prices, we compare the price each customer pays for a given g...

Nowadays most commercial e-shops do not offer any shop assistance or just in a very poor manner. But an e-customer expects guidance and advertising as he or she is used from traditional shops. In this paper we present an approach how personal shopping feeling and individual advertising can be integrated into a shop of the new economy. We show how customer behavior can be described in the prefer...

The general job-shop scheduling problem is known to be extremely hard. We describe a GA approach which produces reasonably good results very quickly on standard benchmark job-shop scheduling problems, better than previous eeorts using genetic algorithms for this task, and comparable to existing conventional search-based methods. The representation used is a variant of one known to work moderate...

This paper addresses the open shop scheduling problem. this problem, due to its complexity, is ranked in the class of NPhard problems. In this case, traditional approaches cannot reach to an optimal solution in a reasonable time. So heuristic algorithms such as simulated Annealing (SA), tabu search (TS) genetic algorithm, (GA), ant colony optimization (ACO) used to solve optimization problems s...

Mass-customization production (MCP) companies must fight with shop-floor uncertainty and complexity caused by wide variety of product components. The research is motivated by a typical MCP company that has experienced inefficient scheduling due to paper-based identification and manual data collection. This paper presents an RFID-enabled real-time manufacturing execution system (RT-MES). RFID de...

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...

The Flexible Job Shop Scheduling Problem (FJSP) is one of the most general and difficult of all traditional scheduling problems. The Flexible Job Shop Problem (FJSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. The problem is to assign each operation to a machine and to order the operations on the machine...