Several recent proposed techniques for multiobjective optimisation use the dominance relation to establish preference among solutions. In this paper, the Pareto archived evolutionary strategy and a population-based annealing algorithm are applied to test instances of a highly constrained combinatorial optimisation problem: academic space allocation. It is shown that the performance of both algo...

Description: Iterative Computer Algorithms with Applications in Engineering describes in-depth the five main iterative algorithms for solving hard combinatorial optimization problems: Simulated Annealing, Genetic Algorithms, Tabu Search, Simulated Evolution, and Stochastic Evolution. The authors present various iterative techniques and illustrate how they can be applied to solve several NP-hard...

Abstract Logistics distribution is a collection of interrelated organizations and facilities. There waste cost time in many links. Therefore, it particularly important to use information technology improve efficiency. Under the constraints delivery vehicle time, this paper proposes an improved genetic simulated annealing algorithm (SAGA), which combines global search ability (GA) (SA) with stro...

the urban waste collection is one of the major municipal activities that involves large expenditures and difficult operational problems. also, waste collection and disposal have high expenses such as investment cost (i.e. vehicles fleet) and high operational cost (i.e. fuel, maintenance). in fact, making slight improvements in this issue lead to a huge saving in municipal consumption. some inci...

task assignment problem (tap) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints. tap is a combinatorial optimization problem and np-complete. this paper proposes a hybrid meta-heuristic algorithm for solving tap in a h...

Make-to-order is a production strategy in which manufacturing starts only after a customer's order is received; in other words, it is a pull-type supply chain operation since manufacturing is carried out as soon as the demand is confirmed. This paper studies the order acceptance problem with weighted tardiness penalties in permutation flow shop scheduling with MTO production strategy, the objec...

Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management. It is an important and strategic operations management problem in supply chain management, and usually involves multiple and conflicting objectives such as cost, service level, resource utilization, etc. This paper proposes a new solution procedure based on genetic algorithms...

The Job Shop Scheduling Problem (JSSP) has enormous industrial applicability. This problem refers to a set of jobs that should be processed in specific order using machines. For the single-objective optimization JSSP problem, Simulated Annealing is among best algorithms. However, Multi-Objective (MOJSSP), these algorithms have barely been analyzed, and Threshold Accepting Algorithm not publishe...

Single row layout is one of the most usually used layout patterns in industries, particularly in flexible manufacturing systems. Here actual sequencing of machine and arrangement of parts, no doubt, have a great influence on the throughput of the flexible manufacturing system i.e., (F.M.S). This paper discusses the single row layout design in flexible manufacturing system (F.M.S). This paper fu...

Optimal operation of multi-reservoir systems is one the most challenging problems in water resource management due to their multi-objective nature and time-consuming solving process. In this paper, Multi-Reservoir Parallel Cellular Automata-Simulated Annealing (MPCA-SA), a hybrid method based on cellular automata simulated annealing presented for bi-objective operations problems. The problem co...