Peerayuth Charnsethikul

Learn More
In this paper, a squared-Euclidean distance multifacility location problem with inseparable demands under balanced transportation constraints is analyzed. Using calculus to project the problem onto the space of allocation variables, the problem becomes minimizing concave quadratic integer programming problem. The algorithm based on extreme point ranking(More)
This paper presents an algorithm combining dynamic programming (DP), benders decomposition and metaheuristics for solving a dynamic facility layout problem. The problem is proposed as an extended model of quadratic assignment problem (QAP) called the dynamic quadratic assignment problem (DQAP). Solving for an optimal solution is extremely difficult since(More)
In this paper, a single-source capacitated multi-facility location problem with rectilinear distance under unbalanced transportation constraints is studied. The problem is formulated as a mixed integer linear programming problem of which the objective function is the sum of nonlinear functions. An algorithm under decomposition approach combining with logic(More)
Problem statement: The objective of this study is to develop efficient exact algorithms for a single source capacitated multi-facility location problem with rectilinear distance. This problem is concerned with locating m capacitated facilities in the two dimensional plane to satisfy the demand of n customers with minimum total transportation cost which is(More)
This paper presents an optimization based heuristic for minimizing makespan on scheduling of n job-groups with q i as the number of identical jobs, p i as the processing time, su i as the setup time required and dd i as the due date, in job-group i through a set of m identical parallel machines. This heuristic, referred as LSCCG, is based on LS(More)
The feed-mix problem is primarily transformed into a mixing situation applying a mathematic formulation with uncertainties. These uncertainties generate the numerous expansions of alternative constraint equations. The given problem has been formulated as mathematic models which correspond to a large-scale Stochastic Programming that cannot be solved by the(More)
A coordinate transformation is proposed to improve the efficiency of the simplex algorithm for solving linear programming problems, and is based on a geometric explanation of phase I to then create a coordinate system whose origin is geometrically close to the optimal solution. Computer simulations on randomly generated and real-world problems are used to e(More)