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Multi-mode resource availability cost problem with recruitment and release dates for resources

Institution:	Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, P. O. Box: 34185-1416, Qazvin, Iran

Abstract:	This paper investigates the multi-mode resource availability cost problem with recruitment and release dates for resources. This problem is a more realistic model and extended case of the resource availability cost problem. The project contains activities interrelated by finish–start precedence relations with zero time lags, which require a set of renewable resources. First, a mixed integer programming formulation is proposed for the problem. Then, simulated annealing (SA) algorithm is proposed to obtain a satisfying solution for this NP-hard problem. The effectiveness of the proposed algorithm is demonstrated through comprehensive experimentation based on 300 test problems. The results are analyzed and discussed.

Keywords:	Project scheduling Multi-mode Investment Simulated annealing SA"} {"#name":"keyword" "$":{"id":"k0610"} "$$":[{"#name":"text" "_":"simulated annealing RCPSP"} {"#name":"keyword" "$":{"id":"k0620"} "$$":[{"#name":"text" "_":"resource constrained project scheduling problem MRCPSP"} {"#name":"keyword" "$":{"id":"k0630"} "$$":[{"#name":"text" "_":"multi-mode resource constrained project scheduling problem RACP"} {"#name":"keyword" "$":{"id":"k0640"} "$$":[{"#name":"text" "_":"resource availability cost problem GA"} {"#name":"keyword" "$":{"id":"k0650"} "$$":[{"#name":"text" "_":"genetic algorithm MRACP-RR"} {"#name":"keyword" "$":{"id":"k0660"} "$$":[{"#name":"text" "_":"multi-mode resource availability cost problem with recruitment and release dates for the resources AON"} {"#name":"keyword" "$":{"id":"k0670"} "$$":[{"#name":"text" "_":"activity on node RK"} {"#name":"keyword" "$":{"id":"k0680"} "$$":[{"#name":"text" "_":"random-key AL"} {"#name":"keyword" "$":{"id":"k0690"} "$$":[{"#name":"text" "_":"activity-list SGS"} {"#name":"keyword" "$":{"id":"k0700"} "$$":[{"#name":"text" "_":"schedule generation scheme SSGS"} {"#name":"keyword" "$":{"id":"k0710"} "$$":[{"#name":"text" "_":"serial schedule generation scheme candidate list restricted candidate list GRPW"} {"#name":"keyword" "$":{"id":"k0740"} "$$":[{"#name":"text" "_":"greatest rank positional weight EST"} {"#name":"keyword" "$":{"id":"k0750"} "$$":[{"#name":"text" "_":"earliest start time EFT"} {"#name":"keyword" "$":{"id":"k0760"} "$$":[{"#name":"text" "_":"earliest finish time LST"} {"#name":"keyword" "$":{"id":"k0770"} "$$":[{"#name":"text" "_":"latest start time LFT"} {"#name":"keyword" "$":{"id":"k0780"} "$$":[{"#name":"text" "_":"latest finish time MSLK"} {"#name":"keyword" "$":{"id":"k0790"} "$$":[{"#name":"text" "_":"minimum slack MTS"} {"#name":"keyword" "$":{"id":"k0800"} "$$":[{"#name":"text" "_":"most total successors SPT"} {"#name":"keyword" "$":{"id":"k0810"} "$$":[{"#name":"text" "_":"shortest processing time WS"} {"#name":"keyword" "$":{"id":"k0820"} "$$":[{"#name":"text" "_":"weighting system RND"} {"#name":"keyword" "$":{"id":"k0830"} "$$":[{"#name":"text" "_":"random selection RLFT"} {"#name":"keyword" "$":{"id":"k0840"} "$$":[{"#name":"text" "_":"random selection with probabilities proportional to LFT NPO"} {"#name":"keyword" "$":{"id":"k0850"} "$$":[{"#name":"text" "$$":[{"#name":"__text__" "_":"number of problems for which Lingo was able to find optimum solution in 1000"} {"#name":"hsp" "$":{"sp":"0 25"}} {"#name":"__text__" "_":"s NPM"} {"#name":"keyword" "$":{"id":"k0860"} "$$":[{"#name":"text" "_":"number of runs of problems for which SA was able to find optimum solution ACNT-L"} {"#name":"keyword" "$":{"id":"k0870"} "$$":[{"#name":"text" "_":"average convergence time for Lingo (in seconds) ACNT-SA"} {"#name":"keyword" "$":{"id":"k0880"} "$$":[{"#name":"text" "_":"average convergence time for the SA (in seconds) ARD"} {"#name":"keyword" "$":{"id":"k0890"} "$$":[{"#name":"text" "_":"average relative deviation percentages
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